Deep Learning Techniques For Biomedical And Health Informatics

Deep Learning Techniques For Biomedical And Health Informatics Book PDF
✏Book Title : Deep Learning Techniques for Biomedical and Health Informatics
✏Author : Dr. Basant Agarwal
✏Publisher : Academic Press
✏Release Date : 2020-01-14
✏Pages : 367
✏ISBN : 9780128190623
✏Available Language : English, Spanish, And French

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✏Deep Learning Techniques for Biomedical and Health Informatics Book Summary : Deep Learning Techniques for Biomedical and Health Informatics provides readers with the state-of-the-art in deep learning-based methods for biomedical and health informatics. The book covers not only the best-performing methods, it also presents implementation methods. The book includes all the prerequisite methodologies in each chapter so that new researchers and practitioners will find it very useful. Chapters go from basic methodology to advanced methods, including detailed descriptions of proposed approaches and comprehensive critical discussions on experimental results and how they are applied to Biomedical Engineering, Electronic Health Records, and medical image processing. Examines a wide range of Deep Learning applications for Biomedical Engineering and Health Informatics, including Deep Learning for drug discovery, clinical decision support systems, disease diagnosis, prediction and monitoring Discusses Deep Learning applied to Electronic Health Records (EHR), including health data structures and management, deep patient similarity learning, natural language processing, and how to improve clinical decision-making Provides detailed coverage of Deep Learning for medical image processing, including optimizing medical big data, brain image analysis, brain tumor segmentation in MRI imaging, and the future of biomedical image analysis

Handbook Of Deep Learning In Biomedical Engineering And Health Informatics Book PDF
✏Book Title : Handbook of Deep Learning in Biomedical Engineering and Health Informatics
✏Author : E Golden Julie
✏Publisher : Apple Academic Press
✏Release Date : 2021-08
✏Pages : 329
✏ISBN : 1771889985
✏Available Language : English, Spanish, And French

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✏Handbook of Deep Learning in Biomedical Engineering and Health Informatics Book Summary : This new volume discusses state-of-the-art deep learning techniques and approaches that can be applied in biomedical systems and health informatics. Deep learning in the biomedical field is an effective method of collecting and analyzing data that can be used for the accurate diagnosis of disease. This volume delves into a variety of applications, techniques, algorithms, platforms, and tools used in this area, such as image segmentation, classification, registration, and computer-aided analysis. The editors proceed on the principle that accurate diagnosis of disease depends on image acquisition and interpretation. There are many methods to get high resolution radiological images, but we are still lacking in automated image interpretation. Currently deep learning techniques are providing a feasible solution for automatic diagnosis of disease with good accuracy. Analyzing clinical data using deep learning techniques enables clinicians to diagnose diseases at an early stage and treat the patients more effectively. Chapters explore such approaches as deep learning algorithms, convolutional neural networks and recurrent neural network architecture, image stitching techniques, deep RNN architectures, and more. The volume also depicts how deep learning techniques can be applied for medical diagnostics of several specific health scenarios, such as cancer, COVID-19, acute neurocutaneous syndrome, cardiovascular and neuro diseases, skin lesions and skin cancer, etc. Key features: Introduces important recent technological advancements in the field Describes the various techniques, platforms, and tools used in biomedical deep learning systems Includes informative case studies that help to explain the new technologies Handbook of Deep Learning in Biomedical Engineering and Health Informatics provides a thorough exploration of biomedical systems applied with deep learning techniques and will provide valuable information for researchers, medical and industry practitioners, academicians, and students.

Predictive Intelligence In Biomedical And Health Informatics Book PDF
✏Book Title : Predictive Intelligence in Biomedical and Health Informatics
✏Author : Rajshree Srivastava
✏Publisher : Walter de Gruyter GmbH & Co KG
✏Release Date : 2020-10-12
✏Pages : 180
✏ISBN : 9783110676143
✏Available Language : English, Spanish, And French

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✏Predictive Intelligence in Biomedical and Health Informatics Book Summary : Predictive Intelligence in Biomedical and Health Informatics focuses on imaging, computer-aided diagnosis and therapy as well as intelligent biomedical image processing and analysis. It develops computational models, methods and tools for biomedical engineering related to computer-aided diagnostics (CAD), computer-aided surgery (CAS), computational anatomy and bioinformatics. Large volumes of complex data are often a key feature of biomedical and engineering problems and computational intelligence helps to address such problems. Practical and validated solutions to hard biomedical and engineering problems can be developed by the applications of neural networks, support vector machines, reservoir computing, evolutionary optimization, biosignal processing, pattern recognition methods and other techniques to address complex problems of the real world.

Future Trends In Biomedical And Health Informatics And Cybersecurity In Medical Devices Book PDF
✏Book Title : Future Trends in Biomedical and Health Informatics and Cybersecurity in Medical Devices
✏Author : Kang-Ping Lin
✏Publisher : Springer Nature
✏Release Date : 2019-09-27
✏Pages : 439
✏ISBN : 9783030306366
✏Available Language : English, Spanish, And French

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✏Future Trends in Biomedical and Health Informatics and Cybersecurity in Medical Devices Book Summary : This book gathers the proceedings of the IV International Conference on Biomedical and Health Informatics (ICBHI 2019), held on 17-20 April, 2019, in Taipei, Taiwan. Contributions span a range of topics, including medical imaging, biosignal processing, biodata management and analytics, public and personalized health systems, mobile health applications and many more. The IV conference edition gave a special emphasis to cybersecurity issues and cutting-edge medical devices, as it is reflected in this book, which provides academics and professionals with extensive knowledge on and a timely snapshot of cutting-edge research and developments in the field of biomedical and health informatics.

The Importance Of Health Informatics In Public Health During A Pandemic Book PDF
✏Book Title : The Importance of Health Informatics in Public Health during a Pandemic
✏Author : J. Mantas
✏Publisher : IOS Press
✏Release Date : 2020-07-24
✏Pages : 520
✏ISBN : 9781643680934
✏Available Language : English, Spanish, And French

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✏The Importance of Health Informatics in Public Health during a Pandemic Book Summary : The COVID-19 pandemic has increased the focus on health informatics and healthcare technology for policy makers and healthcare professionals worldwide. This book contains the 110 papers (from 160 submissions) accepted for the 18th annual International Conference on Informatics, Management, and Technology in Healthcare (ICIMTH 2020), held virtually in Athens, Greece, from 3 – 5 July 2020. The conference attracts scientists working in the field of Biomedical and Health Informatics from all continents, and this year it was held as a Virtual Conference, by means of teleconferencing, due to the COVID-19 pandemic and the consequent lockdown in many countries around the world. The call for papers for the conference started in December 2019, when signs of the new virus infection were not yet evident, so early submissions were on the usual topics as announced. But papers submitted after mid-March were mostly focused on the first results of the pandemic analysis with respect to informatics in different countries and with different perspectives of the spread of the virus and its influence on public health across the world. This book therefore includes papers on the topic of the COVID-19 pandemic in relation to informatics reporting from hospitals and institutions from around the world, including South Korea, Europe, and the USA. The book encompasses the field of biomedical and health informatics in a very broad framework, and the timely inclusion of papers on the current pandemic will make it of particular interest to all those involved in the provision of healthcare everywhere.

📒Medical Imaging ✍ K.C. Santosh

Medical Imaging Book PDF
✏Book Title : Medical Imaging
✏Author : K.C. Santosh
✏Publisher : CRC Press
✏Release Date : 2019-08-20
✏Pages : 238
✏ISBN : 9780429639326
✏Available Language : English, Spanish, And French

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✏Medical Imaging Book Summary : The book discusses varied topics pertaining to advanced or up-to-date techniques in medical imaging using artificial intelligence (AI), image recognition (IR) and machine learning (ML) algorithms/techniques. Further, coverage includes analysis of chest radiographs (chest x-rays) via stacked generalization models, TB type detection using slice separation approach, brain tumor image segmentation via deep learning, mammogram mass separation, epileptic seizures, breast ultrasound images, knee joint x-ray images, bone fracture detection and labeling, and diabetic retinopathy. It also reviews 3D imaging in biomedical applications and pathological medical imaging.

Trends In Deep Learning Methodologies Book PDF
✏Book Title : Trends in Deep Learning Methodologies
✏Author : Vincenzo Piuri
✏Publisher : Academic Press
✏Release Date : 2020-12-15
✏Pages : 306
✏ISBN : 9780128222263
✏Available Language : English, Spanish, And French

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✏Trends in Deep Learning Methodologies Book Summary : Trends in Deep Learning Methodologies: Algorithms, Applications, and Systems covers deep learning approaches such as neural networks, deep belief networks, recurrent neural networks, convolutional neural networks, deep auto-encoder, and deep generative networks, which have emerged as powerful computational models. Chapters elaborate on these models which have shown significant success in dealing with massive data for a large number of applications, given their capacity to extract complex hidden features and learn efficient representation in unsupervised settings. Chapters investigate deep learning-based algorithms in a variety of application, including biomedical and health informatics, computer vision, image processing, and more. In recent years, many powerful algorithms have been developed for matching patterns in data and making predictions about future events. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. Deep learning methods can deal with multiple levels of representation in which the system learns to abstract higher level representations of raw data. Earlier, it was a common requirement to have a domain expert to develop a specific model for each specific application, however, recent advancements in representation learning algorithms allow researchers across various subject domains to automatically learn the patterns and representation of the given data for the development of specific models. Provides insights into the theory, algorithms, implementation and the application of deep learning techniques Covers a wide range of applications of deep learning across smart healthcare and smart engineering Investigates the development of new models and how they can be exploited to find appropriate solutions

Health Informatics Vision From Data Via Information To Knowledge Book PDF
✏Book Title : Health Informatics Vision From Data via Information to Knowledge
✏Author : J. Mantas
✏Publisher : IOS Press
✏Release Date : 2019-08-06
✏Pages : 420
✏ISBN : 9781614999874
✏Available Language : English, Spanish, And French

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✏Health Informatics Vision From Data via Information to Knowledge Book Summary : The latest developments in data, informatics and technology continue to enable health professionals and informaticians to improve healthcare for the benefit of patients everywhere. This book presents full papers from ICIMTH 2019, the 17th International Conference on Informatics, Management and Technology in Healthcare, held in Athens, Greece from 5 to 7 July 2019. Of the 150 submissions received, 95 were selected for presentation at the conference following review and are included here. The conference focused on increasing and improving knowledge of healthcare applications spanning the entire spectrum from clinical and health informatics to public health informatics as applied in the healthcare domain. The field of biomedical and health informatics is examined in a very broad framework, presenting the research and application outcomes of informatics from cell to population and exploring a number of technologies such as imaging, sensors, and biomedical equipment, together with management and organizational aspects including legal and social issues. Setting research priorities in health informatics is also addressed. Providing an overview of the latest developments in health informatics, the book will be of interest to all those working in the field.

Precision Medicine Powered By Phealth And Connected Health Book PDF
✏Book Title : Precision Medicine Powered by pHealth and Connected Health
✏Author : Nicos Maglaveras
✏Publisher : Springer
✏Release Date : 2017-11-16
✏Pages : 269
✏ISBN : 9789811074196
✏Available Language : English, Spanish, And French

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✏Precision Medicine Powered by pHealth and Connected Health Book Summary : This volume presents the proceedings of the 3rd ICBHI which took place in Thessaloniki on 18-21 November, 2017.The area of biomedical and health informatics is exploding at all scales. The developments in the areas of medical devices, eHealth and personalized health as enabling factors for the evolution of precision medicine are quickly developing and demand the development of new scaling tools, integration frameworks and methodologies.

Dhealth 2020 Biomedical Informatics For Health And Care Book PDF
✏Book Title : dHealth 2020 Biomedical Informatics for Health and Care
✏Author : G. Schreier
✏Publisher : IOS Press
✏Release Date : 2020-06-24
✏Pages : 292
✏ISBN : 9781643680859
✏Available Language : English, Spanish, And French

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✏dHealth 2020 Biomedical Informatics for Health and Care Book Summary : Successful digital healthcare depends on the effective flow of a complete chain of information; from the sensor, via multiple steps of processing, to the actuator, which can be anything from a human healthcare professional to a robot. Along this pathway, methods for automating the processing of information, like signal processing, machine learning, predictive analytics and decision support, play an increasing role in providing actionable information and supporting personalized and preventive healthcare concepts in both biomedical and digital healthcare systems and applications. ICT systems in healthcare and biomedical systems and devices are very closely related, and in the future they will become increasingly intertwined. Indeed, it is already often difficult to delineate where the one ends and the other begins. This book presents the intended proceedings of the dHealth 2020 annual conference on the general topic of health Informatics and digital health, which was due to be held in Vienna, Austria, on 19 and 20 May 2020, but which was cancelled due to the COVID-19 pandemic. The decision was nevertheless taken to publish these proceedings, which include the 40 papers which would have been delivered at the conference. The special topic for the 2020 edition of the conference was Biomedical Informatics for Health and Care. The book provides an overview of current developments in health informatics and digital health, and will be of interest to researchers and healthcare practitioners alike.

Computational Intelligence For Machine Learning And Healthcare Informatics Book PDF
✏Book Title : Computational Intelligence for Machine Learning and Healthcare Informatics
✏Author : Rajshree Srivastava
✏Publisher : Walter de Gruyter GmbH & Co KG
✏Release Date : 2020-06-22
✏Pages : 346
✏ISBN : 9783110649277
✏Available Language : English, Spanish, And French

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✏Computational Intelligence for Machine Learning and Healthcare Informatics Book Summary : This book presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. It is intended to provide a unique compendium of current and emerging machine learning paradigms for healthcare informatics, reflecting the diversity, complexity, and depth and breadth of this multi-disciplinary area.

Health Informatics Meets Ehealth Book PDF
✏Book Title : Health Informatics Meets EHealth
✏Author : G. Schreier
✏Publisher : IOS Press
✏Release Date : 2018-05-18
✏Pages : 360
✏ISBN : 9781614998587
✏Available Language : English, Spanish, And French

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✏Health Informatics Meets EHealth Book Summary : Biomedical engineering and health informatics are closely related to each other, and it is often difficult to tell where one ends and the other begins, but ICT systems in healthcare and biomedical systems and devices are already becoming increasingly interconnected, and share the common entity of data. This is something which is set to become even more prevalent in future, and will complete the chain and flow of information from the sensor, via processing, to the actuator, which may be anyone or anything from a human healthcare professional to a robot. Methods for automating the processing of information, such as signal processing, machine learning, predictive analytics and decision support, are increasingly important for providing actionable information and supporting personalized and preventive healthcare protocols in both biomedical and digital healthcare systems and applications. This book of proceedings presents 50 papers from the 12th eHealth conference, eHealth2018, held in Vienna, Austria, in May 2018. The theme of this year’s conference is Biomedical Meets eHealth – From Sensors to Decisions, and the papers included here cover a wide range of topics from the field of eHealth. The book will be of interest to all those working to design and implement healthcare today.

Machine Learning And Medical Imaging Book PDF
✏Book Title : Machine Learning and Medical Imaging
✏Author : Guorong Wu
✏Publisher : Academic Press
✏Release Date : 2016-08-11
✏Pages : 512
✏ISBN : 9780128041147
✏Available Language : English, Spanish, And French

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✏Machine Learning and Medical Imaging Book Summary : Machine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, including not only classical probabilistic modeling and learning methods, but also recent breakthroughs in deep learning, sparse representation/coding, and big data hashing. In the second part leading research groups around the world present a wide spectrum of machine learning methods with application to different medical imaging modalities, clinical domains, and organs. The biomedical imaging modalities include ultrasound, magnetic resonance imaging (MRI), computed tomography (CT), histology, and microscopy images. The targeted organs span the lung, liver, brain, and prostate, while there is also a treatment of examining genetic associations. Machine Learning and Medical Imaging is an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians. Demonstrates the application of cutting-edge machine learning techniques to medical imaging problems Covers an array of medical imaging applications including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics Features self-contained chapters with a thorough literature review Assesses the development of future machine learning techniques and the further application of existing techniques

Machine Learning In Bioinformatics Book PDF
✏Book Title : Machine Learning in Bioinformatics
✏Author : Yanqing Zhang
✏Publisher : John Wiley & Sons
✏Release Date : 2009-02-23
✏Pages : 400
✏ISBN : 0470397411
✏Available Language : English, Spanish, And French

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✏Machine Learning in Bioinformatics Book Summary : An introduction to machine learning methods and their applications to problems in bioinformatics Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. From an internationally recognized panel of prominent researchers in the field, Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics. Coverage includes: feature selection for genomic and proteomic data mining; comparing variable selection methods in gene selection and classification of microarray data; fuzzy gene mining; sequence-based prediction of residue-level properties in proteins; probabilistic methods for long-range features in biosequences; and much more. Machine Learning in Bioinformatics is an indispensable resource for computer scientists, engineers, biologists, mathematicians, researchers, clinicians, physicians, and medical informaticists. It is also a valuable reference text for computer science, engineering, and biology courses at the upper undergraduate and graduate levels.

Deep Learning For Medical Image Analysis Book PDF
✏Book Title : Deep Learning for Medical Image Analysis
✏Author : S. Kevin Zhou
✏Publisher : Academic Press
✏Release Date : 2017-01-18
✏Pages : 458
✏ISBN : 9780128104095
✏Available Language : English, Spanish, And French

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✏Deep Learning for Medical Image Analysis Book Summary : Deep learning is providing exciting solutions for medical image analysis problems and is seen as a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component have been applied to medical image detection, segmentation and registration, and computer-aided analysis, using a wide variety of application areas. Deep Learning for Medical Image Analysis is a great learning resource for academic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Covers common research problems in medical image analysis and their challenges Describes deep learning methods and the theories behind approaches for medical image analysis Teaches how algorithms are applied to a broad range of application areas, including Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc. Includes a Foreword written by Nicholas Ayache

Terahertz Biomedical And Healthcare Technologies Book PDF
✏Book Title : Terahertz Biomedical and Healthcare Technologies
✏Author : Amit Banerjee
✏Publisher : Elsevier
✏Release Date : 2020-08-11
✏Pages : 262
✏ISBN : 9780128185575
✏Available Language : English, Spanish, And French

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✏Terahertz Biomedical and Healthcare Technologies Book Summary : Terahertz Biomedical and Healthcare Technologies: Materials to Devices reviews emerging advances in terahertz biomedical and healthcare technologies, including advances in fundamental materials science research, device design and fabrication, applications, and challenges and opportunities for improved performance. In addition, the improvement of materials, optical elements, and measuring techniques are also explored. Other sections cover the design and development of wide bandgap semiconductors for terahertz device applications, including their physics, device modeling, characterization and fabrication concepts. Finally, the book touches on potential defense, medical imaging, internet of things, and the machine learning applications of terahertz technologies. Reviews the latest advances in the fundamental and applied research of terahertz technologies, covering key topics in materials science, biomedical engineering and healthcare informatics Includes applications of terahertz technologies in medical imaging, diagnosis and treatment Provides readers with an understanding of the machine learning, pattern recognition, and data analytics research utilized to enhance the effectiveness of terahertz technologies

Machine Learning For Health Informatics Book PDF
✏Book Title : Machine Learning for Health Informatics
✏Author : Andreas Holzinger
✏Publisher : Springer
✏Release Date : 2016-12-09
✏Pages : 481
✏ISBN : 9783319504780
✏Available Language : English, Spanish, And French

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✏Machine Learning for Health Informatics Book Summary : Machine learning (ML) is the fastest growing field in computer science, and Health Informatics (HI) is amongst the greatest application challenges, providing future benefits in improved medical diagnoses, disease analyses, and pharmaceutical development. However, successful ML for HI needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. Tackling complex challenges needs both disciplinary excellence and cross-disciplinary networking without any boundaries. Following the HCI-KDD approach, in combining the best of two worlds, it is aimed to support human intelligence with machine intelligence. This state-of-the-art survey is an output of the international HCI-KDD expert network and features 22 carefully selected and peer-reviewed chapters on hot topics in machine learning for health informatics; they discuss open problems and future challenges in order to stimulate further research and international progress in this field.

Medinfo 2017 Precision Healthcare Through Informatics Book PDF
✏Book Title : MEDINFO 2017 Precision Healthcare Through Informatics
✏Author : A.V. Gundlapalli
✏Publisher : IOS Press
✏Release Date : 2018-01-31
✏Pages : 1476
✏ISBN : 9781614998303
✏Available Language : English, Spanish, And French

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✏MEDINFO 2017 Precision Healthcare Through Informatics Book Summary : Medical informatics is a field which continues to evolve with developments and improvements in foundational methods, applications, and technology, constantly offering opportunities for supporting the customization of healthcare to individual patients. This book presents the proceedings of the 16th World Congress of Medical and Health Informatics (MedInfo2017), held in Hangzhou, China, in August 2017, which also marked the 50th anniversary of the International Medical Informatics Association (IMIA). The central theme of MedInfo2017 was "Precision Healthcare through Informatics", and the scientific program was divided into five tracks: connected and digital health; human data science; human, organizational, and social aspects; knowledge management and quality; and safety and patient outcomes. The 249 accepted papers and 168 posters included here span the breadth and depth of sub-disciplines in biomedical and health informatics, such as clinical informatics; nursing informatics; consumer health informatics; public health informatics; human factors in healthcare; bioinformatics; translational informatics; quality and safety; research at the intersection of biomedical and health informatics; and precision medicine. The book will be of interest to all those who wish to keep pace with advances in the science, education, and practice of biomedical and health informatics worldwide.

Machine Learning With Health Care Perspective Book PDF
✏Book Title : Machine Learning with Health Care Perspective
✏Author : Vishal Jain
✏Publisher : Springer Nature
✏Release Date : 2020-03-09
✏Pages : 415
✏ISBN : 9783030408503
✏Available Language : English, Spanish, And French

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✏Machine Learning with Health Care Perspective Book Summary : This unique book introduces a variety of techniques designed to represent, enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. Providing a unique compendium of current and emerging machine learning paradigms for healthcare informatics, it reflects the diversity, complexity, and the depth and breadth of this multi-disciplinary area. Further, it describes techniques for applying machine learning within organizations and explains how to evaluate the efficacy, suitability, and efficiency of such applications. Featuring illustrative case studies, including how chronic disease is being redefined through patient-led data learning, the book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare challenges.

📒Medical Informatics ✍ Hsinchun Chen

Medical Informatics Book PDF
✏Book Title : Medical Informatics
✏Author : Hsinchun Chen
✏Publisher : Springer Science & Business Media
✏Release Date : 2006-07-19
✏Pages : 648
✏ISBN : 9780387257396
✏Available Language : English, Spanish, And French

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✏Medical Informatics Book Summary : Comprehensively presents the foundations and leading application research in medical informatics/biomedicine. The concepts and techniques are illustrated with detailed case studies. Authors are widely recognized professors and researchers in Schools of Medicine and Information Systems from the University of Arizona, University of Washington, Columbia University, and Oregon Health & Science University. Related Springer title, Shortliffe: Medical Informatics, has sold over 8000 copies The title will be positioned at the upper division and graduate level Medical Informatics course and a reference work for practitioners in the field.

Computational Intelligence Methods For Bioinformatics And Biostatistics Book PDF
✏Book Title : Computational Intelligence Methods for Bioinformatics and Biostatistics
✏Author : Francesco Masulli
✏Publisher : Springer Science & Business Media
✏Release Date : 2009-07-14
✏Pages : 294
✏ISBN : 9783642025037
✏Available Language : English, Spanish, And French

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✏Computational Intelligence Methods for Bioinformatics and Biostatistics Book Summary : This volume contains a selection of the best contributions delivered at the 5th InternationalMeetingonComputationalIntelligenceMethodsforBioinformatics andBiostatistics(CIBB 2008)held atIIASS “E. R. Caianiello”,Vietri sul Mare, Salerno, Italy during October 3–4, 2008. The CIBB meeting series is organized by the Special Interest Group on Bioinformatics of the International Neural Network Society (INNS) to provide a forum open to researchersfrom di?erent disciplines to present and discuss pr- lems concerning computational techniques in bioinformatics, systems biology and medical informatics with a particular focus on neural networks, machine learning, fuzzy logic, and evolutionary computational methods. Previous CIBB meetings were held with an increasing number of participants within the f- mat of a special session of larger conferences, namely, WIRN 2004 in Perugia, WILF 2005 in Crema, FLINS 2006 in Genoa and WILF 2007 in Camogli. Given the great success of the special session at WILF 2007 that included 26 papers after a strong selection, the 2008 edition of CIBB was organized, at last, as an autonomous conference, governed by its own Steering Committee. CIBB 2008 attracted 69 paper submissions from all over the world. A r- orous peer-review selection process was applied to ultimately select the papers included in the program of the conference. This volume collects the best cont- butions presented at the conference. Moreover, the volume also includes three presentations from keynote speakers. The success of this conference is to be credited to the contribution of many people.

Signal Processing Techniques For Computational Health Informatics Book PDF
✏Book Title : Signal Processing Techniques for Computational Health Informatics
✏Author : Md Atiqur Rahman Ahad
✏Publisher : Springer Nature
✏Release Date :
✏Pages :
✏ISBN : 9783030549329
✏Available Language : English, Spanish, And French

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✏Signal Processing Techniques for Computational Health Informatics Book Summary :

Bioinformatics And Biomedical Engineering Book PDF
✏Book Title : Bioinformatics and Biomedical Engineering
✏Author : Francisco Ortuño
✏Publisher : Springer
✏Release Date : 2015-03-16
✏Pages : 736
✏ISBN : 9783319164809
✏Available Language : English, Spanish, And French

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✏Bioinformatics and Biomedical Engineering Book Summary : The two volume set LNCS 9043 and 9044 constitutes the refereed proceedings of the Third International Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2015, held in Granada, Spain, in April 2015. The 135 papers presented were carefully reviewed and selected from 268 submissions. The scope of the conference spans the following areas: bioinformatics for healthcare and diseases, biomedical engineering, biomedical image analysis, biomedical signal analysis, computational genomics, computational proteomics, computational systems for modelling biological processes, e Health, next generation sequencing and sequence analysis, quantitative and systems pharmacology, Hidden Markov Model (HMM) for biological sequence modeling, advances in computational intelligence for bioinformatics and biomedicine, tools for next generation sequencing data analysis, dynamics networks in system medicine, interdisciplinary puzzles of measurements in biological systems, biological networks, high performance computing in bioinformatics, computational biology and computational chemistry, advances in drug discovery and ambient intelligence for bio emotional computing.

Introduction To Computational Health Informatics Book PDF
✏Book Title : Introduction to Computational Health Informatics
✏Author : Arvind Kumar Bansal
✏Publisher : CRC Press
✏Release Date : 2020-01-08
✏Pages : 576
✏ISBN : 9781000761597
✏Available Language : English, Spanish, And French

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✏Introduction to Computational Health Informatics Book Summary : This class-tested textbook is designed for a semester-long graduate or senior undergraduate course on Computational Health Informatics. The focus of the book is on computational techniques that are widely used in health data analysis and health informatics and it integrates computer science and clinical perspectives. This book prepares computer science students for careers in computational health informatics and medical data analysis. Features Integrates computer science and clinical perspectives Describes various statistical and artificial intelligence techniques, including machine learning techniques such as clustering of temporal data, regression analysis, neural networks, HMM, decision trees, SVM, and data mining, all of which are techniques used widely used in health-data analysis Describes computational techniques such as multidimensional and multimedia data representation and retrieval, ontology, patient-data deidentification, temporal data analysis, heterogeneous databases, medical image analysis and transmission, biosignal analysis, pervasive healthcare, automated text-analysis, health-vocabulary knowledgebases and medical information-exchange Includes bioinformatics and pharmacokinetics techniques and their applications to vaccine and drug development

Dhealth 2019 From Ehealth To Dhealth Book PDF
✏Book Title : dHealth 2019 From eHealth to dHealth
✏Author : D. Hayn
✏Publisher : IOS Press
✏Release Date : 2019-06-05
✏Pages : 260
✏ISBN : 9781614999713
✏Available Language : English, Spanish, And French

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✏dHealth 2019 From eHealth to dHealth Book Summary : We have all become familiar with the term ‘eHealth’, used to refer to health informatics and the digital aspects of healthcare; but what is dHealth? This book presents the proceedings of the 13th annual conference on Health Informatics Meets Digital Health (dHealth 2019), held in Vienna, Austria, on 28 – 29 May 2019. In keeping with its interdisciplinary mission, the conference series provides a platform for researchers, practitioners, decision makers and vendors to discuss innovative health informatics and eHealth solutions to improve the quality and efficiency of healthcare using digital technologies. The subtitle and special focus of dHealth 2019 is ‘from eHealth to dHealth’, which stresses that healthcare will in future become ever more data-driven. While eHealth in general concerns healthcare IT solutions and professional healthcare providers, dHealth addresses broader fields of application in many areas of life, including sensors and sensor informatics, networks, genomics and bioinformatics, data-centered solutions, machine learning, and many more. The 32 papers included here provide an insight into the state-of-the-art of different aspects of dHealth, including the design and evaluation of user interfaces, patient-centered solutions, electronic health/medical/patient records, machine learning in healthcare and biomedical data analytics, and the book offers the reader an interdisciplinary approach to digital health. It will be of interest to researchers, developers, and healthcare professionals alike.

Data Mining And Medical Knowledge Management Cases And Applications Book PDF
✏Book Title : Data Mining and Medical Knowledge Management Cases and Applications
✏Author : Berka, Petr
✏Publisher : IGI Global
✏Release Date : 2009-02-28
✏Pages : 464
✏ISBN : 9781605662190
✏Available Language : English, Spanish, And French

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✏Data Mining and Medical Knowledge Management Cases and Applications Book Summary : The healthcare industry produces a constant flow of data, creating a need for deep analysis of databases through data mining tools and techniques resulting in expanded medical research, diagnosis, and treatment. Data Mining and Medical Knowledge Management: Cases and Applications presents case studies on applications of various modern data mining methods in several important areas of medicine, covering classical data mining methods, elaborated approaches related to mining in electroencephalogram and electrocardiogram data, and methods related to mining in genetic data. A premier resource for those involved in data mining and medical knowledge management, this book tackles ethical issues related to cost-sensitive learning in medicine and produces theoretical contributions concerning general problems of data, information, knowledge, and ontologies.

Machine Learning For Healthcare Book PDF
✏Book Title : Machine Learning for Healthcare
✏Author : Rashmi Agrawal
✏Publisher : CRC Press
✏Release Date : 2020-12-09
✏Pages : 204
✏ISBN : 9781000221787
✏Available Language : English, Spanish, And French

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✏Machine Learning for Healthcare Book Summary : Machine Learning for Healthcare: Handling and Managing Data provides in-depth information about handling and managing healthcare data through machine learning methods. This book expresses the long-standing challenges in healthcare informatics and provides rational explanations of how to deal with them. Machine Learning for Healthcare: Handling and Managing Data provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of machine learning applications. These are illustrated in a case study which examines how chronic disease is being redefined through patient-led data learning and the Internet of Things. This text offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare. Readers will discover the ethical implications of machine learning in healthcare and the future of machine learning in population and patient health optimization. This book can also help assist in the creation of a machine learning model, performance evaluation, and the operationalization of its outcomes within organizations. It may appeal to computer science/information technology professionals and researchers working in the area of machine learning, and is especially applicable to the healthcare sector. The features of this book include: A unique and complete focus on applications of machine learning in the healthcare sector. An examination of how data analysis can be done using healthcare data and bioinformatics. An investigation of how healthcare companies can leverage the tapestry of big data to discover new business values. An exploration of the concepts of machine learning, along with recent research developments in healthcare sectors.

Medical Informatics In Obstetrics And Gynecology Book PDF
✏Book Title : Medical Informatics in Obstetrics and Gynecology
✏Author : Parry, David
✏Publisher : IGI Global
✏Release Date : 2008-11-30
✏Pages : 428
✏ISBN : 9781605660790
✏Available Language : English, Spanish, And French

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✏Medical Informatics in Obstetrics and Gynecology Book Summary : "This book describes a number of areas within women's health informatics, incorporating a technology perspective"--Provided by publisher.

Contributions To Machine Learning In Biomedical Informatics Book PDF
✏Book Title : Contributions to Machine Learning in Biomedical Informatics
✏Author : Inci Meliha Baytas
✏Publisher :
✏Release Date : 2019
✏Pages : 172
✏ISBN : 1392071321
✏Available Language : English, Spanish, And French

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✏Contributions to Machine Learning in Biomedical Informatics Book Summary : With innovations in digital data acquisition devices and increased memory capacity, virtually all commercial and scientific domains have been witnessing an exponential growth in the amount of data they can collect. For instance, healthcare is experiencing a tremendous growth in digital patient information due to the high adaptation rate of electronic health record systems in hospitals. The abundance of data offers many opportunities to develop robust and versatile systems, as long as the underlying salient information in data can be captured. On the other hand, today's data, often named big data, is challenging to analyze due to its large scale and high complexity. For this reason, efficient data-driven techniques are necessary to extract and utilize the valuable information in the data. The field of machine learning essentially develops such techniques to learn effective models directly from the data. Machine learning models have been successfully employed to solve complicated real world problems. However, the big data concept has numerous properties that pose additional challenges in algorithm development. Namely, high dimensionality, class membership imbalance, non-linearity, distributed data, heterogeneity, and temporal nature are some of the big data characteristics that machine learning must address. Biomedical informatics is an interdisciplinary domain where machine learning techniques are used to analyze electronic health records (EHRs). EHR comprises digital patient data with various modalities and depicts an instance of big data. For this reason, analysis of digital patient data is quite challenging although it provides a rich source for clinical research. While the scale of EHR data used in clinical research might not be huge compared to the other domains, such as social media, it is still not feasible for physicians to analyze and interpret longitudinal and heterogeneous data of thousands of patients. Therefore, computational approaches and graphical tools to assist physicians in summarizing the underlying clinical patterns of the EHRs are necessary. The field of biomedical informatics employs machine learning and data mining approaches to provide the essential computational techniques to analyze and interpret complex healthcare data to assist physicians in patient diagnosis and treatment. In this thesis, we propose and develop machine learning algorithms, motivated by prevalent biomedical informatics tasks, to analyze the EHRs. Specifically, we make the following contributions: (i) A convex sparse principal component analysis approach along with variance reduced stochastic proximal gradient descent is proposed for the patient phenotyping task, which is defined as finding clinical representations for patient groups sharing the same set of diseases. (ii) An asynchronous distributed multi-task learning method is introduced to learn predictive models for distributed EHRs. (iii) A modified long-short term memory (LSTM) architecture is designed for the patient subtyping task, where the goal is to cluster patients based on similar progression pathways. The proposed LSTM architecture, T-LSTM, performs a subspace decomposition on the cell memory such that the short term effect in the previous memory is discounted based on the length of the time gap. (iv) An alternative approach to T-LSTM model is proposed with a decoupled memory to capture the short and long term changes. The proposed model, decoupled memory gated recurrent network (DM-GRN), is designed to learn two types of memories focusing on different components of the time series data. In this study, in addition to the healthcare applications, behavior of the proposed model is investigated for traffic speed prediction problem to illustrate its generalization ability. In summary, the aforementioned machine learning approaches have been developed to address complex characteristics of electronic health records in routine biomedical informatics tasks such as computational patient phenotyping and patient subtyping. Proposed models are also applicable to different domains with similar data characteristics as EHRs.

The Impact Of Digital Technologies On Public Health In Developed And Developing Countries Book PDF
✏Book Title : The Impact of Digital Technologies on Public Health in Developed and Developing Countries
✏Author : Mohamed Jmaiel
✏Publisher : Springer Nature
✏Release Date : 2020-01-01
✏Pages : 442
✏ISBN : 9783030515171
✏Available Language : English, Spanish, And French

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✏The Impact of Digital Technologies on Public Health in Developed and Developing Countries Book Summary : This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2020, held in Hammamet, Tunisia, in June 2020.* The 17 full papers and 23 short papers presented in this volume were carefully reviewed and selected from 49 submissions. They cover topics such as: IoT and AI solutions for e-health; biomedical and health informatics; behavior and activity monitoring; behavior and activity monitoring; and wellbeing technology. *This conference was held virtually due to the COVID-19 pandemic.