Artificial Intelligence And Machine Learning For Healthcare

Author : Ankur Saxena
Publisher : Springer Nature
ISBN 13 : 9811608113
Total Pages : 228 pages
Book Rating : 4.17/5 ( download)

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Download or read book Artificial Intelligence and Machine Learning in Healthcare written by Ankur Saxena and published by Springer Nature. This book was released on 2021-05-06 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the application of artificial intelligence and machine learning in healthcare. It discusses integrating the principles of computer science, life science, and statistics incorporated into statistical models using existing data, discovering patterns in data to extract the information, and predicting the changes and diseases based on this data and models. The initial chapters of the book cover the practical applications of artificial intelligence for disease prognosis & management. Further, the role of artificial intelligence and machine learning is discussed with reference to specific diseases like diabetes mellitus, cancer, mycobacterium tuberculosis, and Covid-19. The chapters provide working examples on how different types of healthcare data can be used to develop models and predict diseases using machine learning and artificial intelligence. The book also touches upon precision medicine, personalized medicine, and transfer learning, with the real examples. Further, it also discusses the use of machine learning and artificial intelligence for visualization, prediction, detection, and diagnosis of Covid -19. This book is a valuable source of information for programmers, healthcare professionals, and researchers interested in understanding the applications of artificial intelligence and machine learning in healthcare.

Author : Arjun Panesar
Publisher : Apress
ISBN 13 : 1484237994
Total Pages : 390 pages
Book Rating : 4.91/5 ( download)

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Download or read book Machine Learning and AI for Healthcare written by Arjun Panesar and published by Apress. This book was released on 2019-02-04 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the theory and practical applications of artificial intelligence (AI) and machine learning in healthcare. This book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare and big data challenges. You’ll discover the ethical implications of healthcare data analytics and the future of AI in population and patient health optimization. You’ll also create a machine learning model, evaluate performance and operationalize its outcomes within your organization. Machine Learning and AI for Healthcare provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of AI applications. These are illustrated through leading case studies, including how chronic disease is being redefined through patient-led data learning and the Internet of Things. What You'll LearnGain a deeper understanding of key machine learning algorithms and their use and implementation within wider healthcare Implement machine learning systems, such as speech recognition and enhanced deep learning/AI Select learning methods/algorithms and tuning for use in healthcare Recognize and prepare for the future of artificial intelligence in healthcare through best practices, feedback loops and intelligent agentsWho This Book Is For Health care professionals interested in how machine learning can be used to develop health intelligence – with the aim of improving patient health, population health and facilitating significant care-payer cost savings.

Author : Eric Topol
Publisher : Basic Books
ISBN 13 : 1541644646
Total Pages : 373 pages
Book Rating : 4.49/5 ( download)

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Download or read book Deep Medicine written by Eric Topol and published by Basic Books. This book was released on 2019-03-12 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Science Friday pick for book of the year, 2019 One of America's top doctors reveals how AI will empower physicians and revolutionize patient care Medicine has become inhuman, to disastrous effect. The doctor-patient relationship--the heart of medicine--is broken: doctors are too distracted and overwhelmed to truly connect with their patients, and medical errors and misdiagnoses abound. In Deep Medicine, leading physician Eric Topol reveals how artificial intelligence can help. AI has the potential to transform everything doctors do, from notetaking and medical scans to diagnosis and treatment, greatly cutting down the cost of medicine and reducing human mortality. By freeing physicians from the tasks that interfere with human connection, AI will create space for the real healing that takes place between a doctor who can listen and a patient who needs to be heard. Innovative, provocative, and hopeful, Deep Medicine shows us how the awesome power of AI can make medicine better, for all the humans involved.

Author : Adam Bohr
Publisher : Academic Press
ISBN 13 : 0128184396
Total Pages : 385 pages
Book Rating : 4.94/5 ( download)

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Download or read book Artificial Intelligence in Healthcare written by Adam Bohr and published by Academic Press. This book was released on 2020-06-21 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 : KC Santosh
Publisher : Springer Nature
ISBN 13 : 9811667683
Total Pages : 93 pages
Book Rating : 4.88/5 ( download)

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Download or read book Artificial Intelligence and Machine Learning in Public Healthcare written by KC Santosh and published by Springer Nature. This book was released on 2022-01-01 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses and evaluates AI and machine learning (ML) algorithms in dealing with challenges that are primarily related to public health. It also helps find ways in which we can measure possible consequences and societal impacts by taking the following factors into account: open public health issues and common AI solutions (with multiple case studies, such as TB and SARS: COVID-19), AI in sustainable health care, AI in precision medicine and data privacy issues. Public health requires special attention as it drives economy and education system. COVID-19 is an example—a truly infectious disease outbreak. The vision of WHO is to create public health services that can deal with abovementioned crucial challenges by focusing on the following elements: health protection, disease prevention and health promotion. For these issues, in the big data analytics era, AI and ML tools/techniques have potential to improve public health (e.g., existing healthcare solutions and wellness services). In other words, they have proved to be valuable tools not only to analyze/diagnose pathology but also to accelerate decision-making procedure especially when we consider resource-constrained regions.

Author : Arman Kilic
Publisher : Academic Press
ISBN 13 : 012822519X
Total Pages : 0 pages
Book Rating : 4.96/5 ( download)

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Download or read book Artificial Intelligence and Machine Learning in Healthcare written by Arman Kilic and published by Academic Press. This book was released on 2024-10-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence and Machine Learning in Healthcare discusses the potential of groundbreaking technologies on the delivery of care. A lot have been said about how artificial intelligence and machine learning can improve healthcare, however there are still many doubts and concerns among health professionals, all of which are addressed in this book. Sections cover History and Basic Overview of AI and ML, with differentiation of supervised, unsupervised and deep learning, Applications of AI and ML in Healthcare, The Future of Healthcare with AI, Challenges to Adopting AI in Healthcare, and ethics and legal processes for implementation. This book is a valuable resource for bioinformaticians, clinicians, graduate students and several members of biomedical field who needs to get up to speed on the revolutionary role of AI and Machine Learning in healthcare. Provides an overview of AI and ML to the medical practitioner who may not be well versed in these fields Encompasses a thorough review of what has been accomplished and demonstrated recently in the fields of AI and ML in healthcare Discusses the future of AI and ML in healthcare, with a review of possible wearable technology and software and how they may be used for medical care

Author : Rabinarayan Satpathy
Publisher : John Wiley & Sons
ISBN 13 : 111978560X
Total Pages : 433 pages
Book Rating : 4.06/5 ( download)

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Download or read book Data Analytics in Bioinformatics written by Rabinarayan Satpathy and published by John Wiley & Sons. This book was released on 2021-01-20 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning 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. Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics approximating classification and prediction of disease, feature selection, dimensionality reduction, gene selection and classification of microarray data and many more.

Author : Mitul Kumar Ahirwal
Publisher : CRC Press
ISBN 13 : 1000570304
Total Pages : 332 pages
Book Rating : 4.04/5 ( download)

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Download or read book Artificial Intelligence Applications for Health Care written by Mitul Kumar Ahirwal and published by CRC Press. This book was released on 2022-04-15 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book takes an interdisciplinary approach by covering topics on health care and artificial intelligence. Data sets related to biomedical signals (ECG, EEG, EMG) and images (X-rays, MRI, CT) are explored, analyzed, and processed through different computation intelligence methods. Applications of computational intelligence techniques like artificial and deep neural networks, swarm optimization, expert systems, decision support systems, clustering, and classification techniques on medial datasets are explained. Survey of medical signals, medial images, and computation intelligence methods are also provided in this book. Key Features Covers computational Intelligence techniques like artificial neural networks, deep neural networks, and optimization algorithms for Healthcare systems Provides easy understanding for concepts like signal and image filtering techniques Includes discussion over data preprocessing and classification problems Details studies with medical signal (ECG, EEG, EMG) and image (X-ray, FMRI, CT) datasets Describes evolution parameters such as accuracy, precision, and recall etc. This book is aimed at researchers and graduate students in medical signal and image processing, machine and deep learning, and healthcare technologies.

Author : Gyorgy J. Simon
Publisher : Springer Nature
ISBN 13 : 3031393554
Total Pages : 824 pages
Book Rating : 4.56/5 ( download)

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Download or read book Artificial Intelligence and Machine Learning in Health Care and Medical Sciences written by Gyorgy J. Simon and published by Springer Nature. This book was released on with total page 824 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : Yen-Wei Chen
Publisher : Springer Nature
ISBN 13 : 3030326063
Total Pages : 225 pages
Book Rating : 4.67/5 ( download)

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Download or read book Deep Learning in Healthcare written by Yen-Wei Chen and published by Springer Nature. This book was released on 2019-11-18 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems. Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academic and industrial areas. DL involves using a neural network with many layers (deep structure) between input and output, and its main advantage of is that it can automatically learn data-driven, highly representative and hierarchical features and perform feature extraction and classification on one network. DL can be used to model or simulate an intelligent system or process using annotated training data. Recently, DL has become widely used in medical applications, such as anatomic modelling, tumour detection, disease classification, computer-aided diagnosis and surgical planning. This book is intended for computer science and engineering students and researchers, medical professionals and anyone interested using DL techniques.