Artificial Intelligence (AI) in Health Sciences

The potential of AI to improve healthcare delivery and patient outcomes has led to increasing application of AI techniques such as deep learning, computer vision, natural language processing, and robotics.

Designed as a self-teaching introduction to the fundamental concepts of artificial intelligence, the book begins with its history, the Turing test, and early applications.

This book presents a systematic evolution of artificial intelligence (AI), its applications, challenges and solutions in the field of healthcare.

This book elaborates in detail on the current needs of data mining and machine learning and promotes mutual understanding among research in different disciplines.

This updated second edition offers a guided tour of machine learning algorithms and architecture design. It provides real-world applications of intelligent systems in healthcare and covers the challenges of managing big data.

At the dawn of the 4th Industrial Revolution, the field of Deep Learning (a sub-field of Artificial Intelligence and Machine Learning) is growing continuously and rapidly, developing both theoretically and towards applications in increasingly many and diverse other disciplines.

Predictive Medicine makes artificial intelligence more accessible for healthcare practitioners without shying away from complex topics and controversial subject matter.

This book presents recent work on healthcare management and engineering using artificial intelligence and data mining techniques.

in Artificial Intelligence In Medicine.

in Journal of Clinical Nursing.

in Academic Medicine.

in JAMA Internal Medicine.

in BMC Medical Research Methodology.

in PLOS Digital Health.

in BMC Medical Education.

in JACCP.

in American Journal of Pharmaceutical Education.

in Scientometrics.

in Artificial Intelligence In Medicine.