Optimized Predictive Models In Health Care Using Machine Learning

Author : Sandeep Kumar,Anuj Sharma,Navneet Kaur,Lokesh Pawar,Rohit Bajaj
Publisher : John Wiley & Sons
Page : 388 pages
File Size : 41,5 Mb
Release : 2024-02-08
Category : Computers
ISBN : 9781394175352

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Optimized Predictive Models in Health Care Using Machine Learning by Sandeep Kumar,Anuj Sharma,Navneet Kaur,Lokesh Pawar,Rohit Bajaj Pdf

OPTIMIZED PREDICTIVE MODELS IN HEALTH CARE USING MACHINE LEARNING This book is a comprehensive guide to developing and implementing optimized predictive models in healthcare using machine learning and is a required resource for researchers, healthcare professionals, and students who wish to know more about real-time applications. The book focuses on how humans and computers interact to ever-increasing levels of complexity and simplicity and provides content on the theory of optimized predictive model design, evaluation, and user diversity. Predictive modeling, a field of machine learning, has emerged as a powerful tool in healthcare for identifying high-risk patients, predicting disease progression, and optimizing treatment plans. By leveraging data from various sources, predictive models can help healthcare providers make informed decisions, resulting in better patient outcomes and reduced costs. Other essential features of the book include: provides detailed guidance on data collection and preprocessing, emphasizing the importance of collecting accurate and reliable data; explains how to transform raw data into meaningful features that can be used to improve the accuracy of predictive models; gives a detailed overview of machine learning algorithms for predictive modeling in healthcare, discussing the pros and cons of different algorithms and how to choose the best one for a specific application; emphasizes validating and evaluating predictive models; provides a comprehensive overview of validation and evaluation techniques and how to evaluate the performance of predictive models using a range of metrics; discusses the challenges and limitations of predictive modeling in healthcare; highlights the ethical and legal considerations that must be considered when developing predictive models and the potential biases that can arise in those models. Audience The book will be read by a wide range of professionals who are involved in healthcare, data science, and machine learning.

Author : Leo Anthony Celi,Maimuna S. Majumder,Patricia Ordóñez,Juan Sebastian Osorio,Kenneth E. Paik,Melek Somai
Publisher : Springer Nature
Page : 471 pages
File Size : 48,9 Mb
Release : 2020-07-31
Category : Medical
ISBN : 9783030479947

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Leveraging Data Science for Global Health by Leo Anthony Celi,Maimuna S. Majumder,Patricia Ordóñez,Juan Sebastian Osorio,Kenneth E. Paik,Melek Somai Pdf

This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emerging infectious disease outbreaks due to disruption of ecosystems, civil unrest, and poor healthcare infrastructure – and without comprehensive surveillance, delays in outbreak identification, resource deployment, and case management can be catastrophic. In combination with context-informed analytics, students will learn how non-traditional digital disease data sources – including news media, social media, Google Trends, and Google Street View – can fill critical knowledge gaps and help inform on-the-ground decision-making when formal surveillance systems are insufficient.

Author : Dinesh Kumar
Publisher : Unknown
Page : 0 pages
File Size : 53,8 Mb
Release : 2023-07-03
Category : Electronic
ISBN : 0930384857

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Smart Predictive Healthcare Using Machine Learning Techniques by Dinesh Kumar Pdf

Author : Vishal Jain,Jyotir Moy Chatterjee
Publisher : Springer Nature
Page : 418 pages
File Size : 42,7 Mb
Release : 2020-03-09
Category : Technology & Engineering
ISBN : 9783030408503

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Machine Learning with Health Care Perspective by Vishal Jain,Jyotir Moy Chatterjee Pdf

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.

Author : Sudipta Roy,Lalit Mohan Goyal,Mamta Mittal
Publisher : Springer Nature
Page : 317 pages
File Size : 43,8 Mb
Release : 2021-04-22
Category : Technology & Engineering
ISBN : 9789811605383

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Advanced Prognostic Predictive Modelling in Healthcare Data Analytics by Sudipta Roy,Lalit Mohan Goyal,Mamta Mittal Pdf

This book discusses major technical advancements and research findings in the field of prognostic modelling in healthcare image and data analysis. The use of prognostic modelling as predictive models to solve complex problems of data mining and analysis in health care is the feature of this book. The book examines the recent technologies and studies that reached the practical level and becoming available in preclinical and clinical practices in computational intelligence. The main areas of interest covered in this book are highest quality, original work that contributes to the basic science of processing, analysing and utilizing all aspects of advanced computational prognostic modelling in healthcare image and data analysis.

Author : Gyorgy J. Simon
Publisher : Springer Nature
Page : 824 pages
File Size : 55,5 Mb
Release : 2024-06-26
Category : Electronic
ISBN : 9783031393556

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Artificial Intelligence and Machine Learning in Health Care and Medical Sciences by Gyorgy J. Simon Pdf

Author : Cao Xiao,Jimeng Sun
Publisher : Springer Nature
Page : 236 pages
File Size : 46,7 Mb
Release : 2021-11-11
Category : Medical
ISBN : 9783030821845

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Introduction to Deep Learning for Healthcare by Cao Xiao,Jimeng Sun Pdf

This textbook presents deep learning models and their healthcare applications. It focuses on rich health data and deep learning models that can effectively model health data. Healthcare data: Among all healthcare technologies, electronic health records (EHRs) had vast adoption and a significant impact on healthcare delivery in recent years. One crucial benefit of EHRs is to capture all the patient encounters with rich multi-modality data. Healthcare data include both structured and unstructured information. Structured data include various medical codes for diagnoses and procedures, lab results, and medication information. Unstructured data contain 1) clinical notes as text, 2) medical imaging data such as X-rays, echocardiogram, and magnetic resonance imaging (MRI), and 3) time-series data such as the electrocardiogram (ECG) and electroencephalogram (EEG). Beyond the data collected during clinical visits, patient self-generated/reported data start to grow thanks to wearable sensors’ increasing use. The authors present deep learning case studies on all data described. Deep learning models: Neural network models are a class of machine learning methods with a long history. Deep learning models are neural networks of many layers, which can extract multiple levels of features from raw data. Deep learning applied to healthcare is a natural and promising direction with many initial successes. The authors cover deep neural networks, convolutional neural networks, recurrent neural networks, embedding methods, autoencoders, attention models, graph neural networks, memory networks, and generative models. It’s presented with concrete healthcare case studies such as clinical predictive modeling, readmission prediction, phenotyping, x-ray classification, ECG diagnosis, sleep monitoring, automatic diagnosis coding from clinical notes, automatic deidentification, medication recommendation, drug discovery (drug property prediction and molecule generation), and clinical trial matching. This textbook targets graduate-level students focused on deep learning methods and their healthcare applications. It can be used for the concepts of deep learning and its applications as well. Researchers working in this field will also find this book to be extremely useful and valuable for their research.

Author : Akash Kumar Bhoi,Ranjit Panigrahi,Victor, Hugo C. de Albuquerque,Rutvij H. Jhaveri
Publisher : Walter de Gruyter GmbH & Co KG
Page : 354 pages
File Size : 51,6 Mb
Release : 2024-03-18
Category : Computers
ISBN : 9783110750942

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Healthcare Big Data Analytics by Akash Kumar Bhoi,Ranjit Panigrahi,Victor, Hugo C. de Albuquerque,Rutvij H. Jhaveri Pdf

This book highlights how optimized big data applications can be used for patient monitoring and clinical diagnosis. In fact, IoT-based applications are data-driven and mostly employ modern optimization techniques. The book also explores challenges, opportunities, and future research directions, discussing the stages of data collection and pre-processing, as well as the associated challenges and issues in data handling and setup.

Author : Rashmi Agrawal,Jyotir Moy Chatterjee,Abhishek Kumar,Pramod Singh Rathore,Dac-Nhuong Le
Publisher : CRC Press
Page : 160 pages
File Size : 50,7 Mb
Release : 2020-12-08
Category : Computers
ISBN : 9781000221886

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Machine Learning for Healthcare by Rashmi Agrawal,Jyotir Moy Chatterjee,Abhishek Kumar,Pramod Singh Rathore,Dac-Nhuong Le Pdf

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.

Author : Malek Masmoudi,Bassem Jarboui,Patrick Siarry
Publisher : Springer Nature
Page : 211 pages
File Size : 43,5 Mb
Release : 2021-01-25
Category : Computers
ISBN : 9783030452407

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Artificial Intelligence and Data Mining in Healthcare by Malek Masmoudi,Bassem Jarboui,Patrick Siarry Pdf

This book presents recent work on healthcare management and engineering using artificial intelligence and data mining techniques. Specific topics covered in the contributed chapters include predictive mining, decision support, capacity management, patient flow optimization, image compression, data clustering, and feature selection. The content will be valuable for researchers and postgraduate students in computer science, information technology, industrial engineering, and applied mathematics.

Author : Adam Bohr,Kaveh Memarzadeh
Publisher : Academic Press
Page : 385 pages
File Size : 41,9 Mb
Release : 2020-06-21
Category : Computers
ISBN : 9780128184394

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Artificial Intelligence in Healthcare by Adam Bohr,Kaveh Memarzadeh Pdf

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data

Author : Sachi Nandan Mohanty,G. Nalinipriya,Om Prakash Jena,Achyuth Sarkar
Publisher : John Wiley & Sons
Page : 418 pages
File Size : 52,9 Mb
Release : 2021-04-13
Category : Computers
ISBN : 9781119791812

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Machine Learning for Healthcare Applications by Sachi Nandan Mohanty,G. Nalinipriya,Om Prakash Jena,Achyuth Sarkar Pdf

When considering the idea of using machine learning in healthcare, it is a Herculean task to present the entire gamut of information in the field of intelligent systems. It is, therefore the objective of this book to keep the presentation narrow and intensive. This approach is distinct from others in that it presents detailed computer simulations for all models presented with explanations of the program code. It includes unique and distinctive chapters on disease diagnosis, telemedicine, medical imaging, smart health monitoring, social media healthcare, and machine learning for COVID-19. These chapters help develop a clear understanding of the working of an algorithm while strengthening logical thinking. In this environment, answering a single question may require accessing several data sources and calling on sophisticated analysis tools. While data integration is a dynamic research area in the database community, the specific needs of research have led to the development of numerous middleware systems that provide seamless data access in a result-driven environment. Since this book is intended to be useful to a wide audience, students, researchers and scientists from both academia and industry may all benefit from this material. It contains a comprehensive description of issues for healthcare data management and an overview of existing systems, making it appropriate for introductory and instructional purposes. Prerequisites are minimal; the readers are expected to have basic knowledge of machine learning. This book is divided into 22 real-time innovative chapters which provide a variety of application examples in different domains. These chapters illustrate why traditional approaches often fail to meet customers’ needs. The presented approaches provide a comprehensive overview of current technology. Each of these chapters, which are written by the main inventors of the presented systems, specifies requirements and provides a description of both the chosen approach and its implementation. Because of the self-contained nature of these chapters, they may be read in any order. Each of the chapters use various technical terms which involve expertise in machine learning and computer science.

Author : Poonam Tanwar,Vishal Jain,Chuan-Ming Liu,Vishal Goyal
Publisher : Emerald Group Publishing
Page : 252 pages
File Size : 45,6 Mb
Release : 2020-09-30
Category : Business & Economics
ISBN : 9781839091018

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Big Data Analytics and Intelligence by Poonam Tanwar,Vishal Jain,Chuan-Ming Liu,Vishal Goyal Pdf

Big Data Analytics and Intelligence is essential reading for researchers and experts working in the fields of health care, data science, analytics, the internet of things, and information retrieval.

Author : Himani Bansal,Balamurugan Balusamy,T. Poongodi,Firoz Khan KP
Publisher : CRC Press
Page : 275 pages
File Size : 43,8 Mb
Release : 2021-06-30
Category : Technology & Engineering
ISBN : 9781000406191

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Machine Learning and Analytics in Healthcare Systems by Himani Bansal,Balamurugan Balusamy,T. Poongodi,Firoz Khan KP Pdf

Bridges the gap between engineering and medicine in combining the design and problem solving skills of engineering with health sciences Explores real-world case studies in machine learning and healthcare analytics Presents a detailed exploration of applications of machine learning in healthcare systems Provides readers with how the industry avoids some of the consequences of old methods of data sharing strategies Offers readers multiple perspectives on a variety of disciplines

Author : Hrudaya Kumar Tripathy,Sushruta Mishra,Pradeep Kumar Mallick,Amiya Ranjan Panda
Publisher : Springer Nature
Page : 393 pages
File Size : 53,6 Mb
Release : 2021-02-27
Category : Technology & Engineering
ISBN : 9789813346987

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Technical Advancements of Machine Learning in Healthcare by Hrudaya Kumar Tripathy,Sushruta Mishra,Pradeep Kumar Mallick,Amiya Ranjan Panda Pdf

This book focuses on various advanced technologies which integrate with machine learning to assist one of the most leading industries, healthcare. It presents recent research works based on machine learning approaches supported by medical and information communication technologies with the use of data and image analysis. The book presents insight about techniques which broadly deals in delivery of quality, accurate and affordable healthcare solutions by predictive, proactive and preventative methods. The book also explores the possible use of machine learning in enterprises, such as enhanced medical imaging/diagnostics, understanding medical data, drug discovery and development, robotic surgery and automation, radiation treatments, creating electronic smart records and outbreak prediction.