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Author: Li Zhang Publisher: Frontiers Media SA ISBN: 283255055X Category : Science Languages : en Pages : 149
Book Description
Large databases are created by genomics for the discovery, study, and development of novel treatments all around the world. It's not hard to conceive that artificial intelligence (AI) might currently study the 3 billion base pairs that make up humanoid genetic makeup in order to uncover genetic disparities among the population. By 2026, large pharmaceutical companies hope to have researched up to 2 million genomes and analyzed massive amounts of patient data from clinical drug studies. As new equipment is introduced, AI will be employed in genomics for a variety of omics investigations, including transcriptomics. To aid in the classification of potentially clinically significant genes, AI is used to combine data from genomic research with literature analysis. Machine learning is now a critical component of the genomics industry's growth. AI and Machine learning in genomics is already having an impact on a number of areas, including genetic testing, medical care delivery, and genomics accessibility for people interested in learning more about how their genes influence their health. The purpose of this research is to explore AI and Machine learning applications in gene technology and their roles in paving the way for future genomics machine learning applications.
Author: Li Zhang Publisher: Frontiers Media SA ISBN: 283255055X Category : Science Languages : en Pages : 149
Book Description
Large databases are created by genomics for the discovery, study, and development of novel treatments all around the world. It's not hard to conceive that artificial intelligence (AI) might currently study the 3 billion base pairs that make up humanoid genetic makeup in order to uncover genetic disparities among the population. By 2026, large pharmaceutical companies hope to have researched up to 2 million genomes and analyzed massive amounts of patient data from clinical drug studies. As new equipment is introduced, AI will be employed in genomics for a variety of omics investigations, including transcriptomics. To aid in the classification of potentially clinically significant genes, AI is used to combine data from genomic research with literature analysis. Machine learning is now a critical component of the genomics industry's growth. AI and Machine learning in genomics is already having an impact on a number of areas, including genetic testing, medical care delivery, and genomics accessibility for people interested in learning more about how their genes influence their health. The purpose of this research is to explore AI and Machine learning applications in gene technology and their roles in paving the way for future genomics machine learning applications.
Author: Adam Bohr Publisher: Academic Press ISBN: 0128184396 Category : Computers Languages : en Pages : 385
Book Description
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: Michael Mahler Publisher: Academic Press ISBN: 032385432X Category : Science Languages : en Pages : 302
Book Description
Precision Medicine and Artificial Intelligence: The Perfect Fit for Autoimmunity covers background on artificial intelligence (AI), its link to precision medicine (PM), and examples of AI in healthcare, especially autoimmunity. The book highlights future perspectives and potential directions as AI has gained significant attention during the past decade. Autoimmune diseases are complex and heterogeneous conditions, but exciting new developments and implementation tactics surrounding automated systems have enabled the generation of large datasets, making autoimmunity an ideal target for AI and precision medicine. More and more diagnostic products utilize AI, which is also starting to be supported by regulatory agencies such as the Food and Drug Administration (FDA). Knowledge generation by leveraging large datasets including demographic, environmental, clinical and biomarker data has the potential to not only impact the diagnosis of patients, but also disease prediction, prognosis and treatment options. - Allows the readers to gain an overview on precision medicine for autoimmune diseases leveraging AI solutions - Provides background, milestone and examples of precision medicine - Outlines the paradigm shift towards precision medicine driven by value-based systems - Discusses future applications of precision medicine research using AI - Other aspects covered in the book include regulatory insights, data analytics and visualization, types of biomarkers as well as the role of the patient in precision medicine
Author: Jason Baron Publisher: Elsevier Health Sciences ISBN: 0323939848 Category : Medical Languages : en Pages : 161
Book Description
In this issue, guest editors bring their considerable expertise to this important topic.Provides in-depth reviews on the latest updates in the field, providing actionable insights for clinical practice. Presents the latest information on this timely, focused topic under the leadership of experienced editors in the field. Authors synthesize
Author: Eric Topol Publisher: Basic Books ISBN: 1541644646 Category : Health & Fitness Languages : en Pages : 388
Book Description
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: Markus D. Dubber Publisher: Oxford University Press ISBN: 0190067411 Category : Law Languages : en Pages : 1000
Book Description
This volume tackles a quickly-evolving field of inquiry, mapping the existing discourse as part of a general attempt to place current developments in historical context; at the same time, breaking new ground in taking on novel subjects and pursuing fresh approaches. The term "A.I." is used to refer to a broad range of phenomena, from machine learning and data mining to artificial general intelligence. The recent advent of more sophisticated AI systems, which function with partial or full autonomy and are capable of tasks which require learning and 'intelligence', presents difficult ethical questions, and has drawn concerns from many quarters about individual and societal welfare, democratic decision-making, moral agency, and the prevention of harm. This work ranges from explorations of normative constraints on specific applications of machine learning algorithms today-in everyday medical practice, for instance-to reflections on the (potential) status of AI as a form of consciousness with attendant rights and duties and, more generally still, on the conceptual terms and frameworks necessarily to understand tasks requiring intelligence, whether "human" or "A.I."
Author: Chayakrit Krittanawong Publisher: Elsevier ISBN: 0443156891 Category : Computers Languages : en Pages : 550
Book Description
Artificial Intelligence in Clinical Practice: How AI Technologies Impact Medical Research and Clinics compiles current research on Artificial Intelligence within medical subspecialties, helping practitioners with diagnosis, clinical decision-making, disease prediction, prevention, and the facilitation of precision medicine. The book defines the basic concepts of big data and AI in medicine and highlights current applications, challenges, ethical issues, and biases. Each chapter discusses AI applied to a specific medical subspecialty, including primary care, preventive medicine, general internal medicine, radiology, pathology, infectious disease, gastroenterology, cardiology, hematology, oncology, dermatology, ophthalmology, mental health, neurology, pulmonary, critical care, rheumatology, surgery, and OB-GYN. This is a valuable resource for clinicians, students, researchers and members of medical and biomedical fields who are interested in learning more about artificial intelligence technologies and their applications in medicine. Provides the history and overview of the various modalities of AI and their applications within each field of medicine Discusses current AI-based medical research, including landmark trials within each field of medicine Addresses the current knowledge gaps that clinicians commonly face that prevent the application of AI-based research to clinical practice Encompasses examples of specific cases and discusses challenges and biases associated with AI
Author: Alexey Karpov Publisher: Springer ISBN: 3319664298 Category : Computers Languages : en Pages : 845
Book Description
This book constitutes the proceedings of the 19th International Conference on Speech and Computer, SPECOM 2017, held in Hatfield, UK, in September 2017. The 80 papers presented in this volume were carefully reviewed and selected from 150 submissions. The papers present current research in the area of computer speech processing (recognition, synthesis, understanding etc.) and related domains (including signal processing, language and text processing, computational paralinguistics, multi-modal speech processing, human-computer interaction).
Author: Gary D. Miner Publisher: Academic Press ISBN: 0323952755 Category : Computers Languages : en Pages : 578
Book Description
Practical Data Analytics for Innovation in Medicine: Building Real Predictive and Prescriptive Models in Personalized Healthcare and Medical Research Using AI, ML, and Related Technologies, Second Edition discusses the needs of healthcare and medicine in the 21st century, explaining how data analytics play an important and revolutionary role. With healthcare effectiveness and economics facing growing challenges, there is a rapidly emerging movement to fortify medical treatment and administration by tapping the predictive power of big data, such as predictive analytics, which can bolster patient care, reduce costs, and deliver greater efficiencies across a wide range of operational functions. Sections bring a historical perspective, highlight the importance of using predictive analytics to help solve health crisis such as the COVID-19 pandemic, provide access to practical step-by-step tutorials and case studies online, and use exercises based on real-world examples of successful predictive and prescriptive tools and systems. The final part of the book focuses on specific technical operations related to quality, cost-effective medical and nursing care delivery and administration brought by practical predictive analytics. Brings a historical perspective in medical care to discuss both the current status of health care delivery worldwide and the importance of using modern predictive analytics to help solve the health care crisis Provides online tutorials on several predictive analytics systems to help readers apply their knowledge on today’s medical issues and basic research Teaches how to develop effective predictive analytic research and to create decisioning/prescriptive analytic systems to make medical decisions quicker and more accurate
Author: Li Zhang
Author: Li Zhang
Author: Deepak Kumar Jain
Author: Adam Bohr
Author: Michael Mahler
Author: Jason Baron
Author: Eric Topol
Author: Markus D. Dubber
Author: Chayakrit Krittanawong
Author: Alexey Karpov
Author: Gary D. Miner