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Sinopsis
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 Learn
- Gain 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 agents
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.
"Sinopsis" puede pertenecer a otra edición de este libro.
Acerca del autor
Arjun Panesar is the founder of Diabetes Digital Media (DDM), the world’s largest diabetes community and provider of evidence-based digital health interventions. Arjun holds a first-class honors degree (MEng) in Computing and Artificial Intelligence from Imperial College, London. Benefiting from a decade of experience in big data and affecting user outcomes, Arjun leads the development of intelligent, evidence-based digital health interventions that harness the power of big data and machine learning to provide precision patient care to patients, health agencies and governments worldwide.
De la contraportada
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.
Youll discover the ethical implications of healthcare data analytics and the future of AI in population and patient health optimization. Youll 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.
"Sobre este título" puede pertenecer a otra edición de este libro.
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Machine Learning and Ai for Healthcare: Big Data for Improved Health Outcomes
Librería: Revaluation Books, Exeter, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: Brand New. 368 pages. 9.00x6.00x0.75 inches. In Stock. Nº de ref. del artículo: zk1484237986
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Machine Learning and AI for Healthcare
Librería: HPB-Diamond, Dallas, TX, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
paperback. Condición: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority! Nº de ref. del artículo: S_440634318
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Machine Learning and AI for Healthcare
Librería: Blue Vase Books, Interlochen, MI, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Condición: acceptable. The item is very worn but is perfectly usable. Signs of wear can include aesthetic issues such as scratches, dents, worn and creased covers, folded page corners and minor liquid stains. All pages and the cover are intact, but the dust cover may be missing. Pages may include moderate to heavy amount of notes and highlighting, but the text is not obscured or unreadable. Page edges may have foxing age related spots and browning . May NOT include discs, access code or other supplemental materials. Nº de ref. del artículo: BVV.1484237986.A
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