Chapter 6AI in Healthcare

It's estimated that every patient will generate enough health data to fill nearly 300 million books in his or her lifetime. Meanwhile, research is expanding so rapidly that it would take physicians 150 hours a week to read everything published in their field … Machine learning has the potential to complement (not replace) healthcare providers and scientists.

Dr. Jonathan Lewin, CEO of Emory Healthcare, and Dr. Jeffrey Balser, CEO of Vanderbilt University Medical Center

The current state of AI in healthcare is a combination of brilliant successes, enormous potential, and a fair degree of frustration. The amount of data available to help physicians and medical researchers diagnose and treat illness is considerable, but existing systems can be fragmented and difficult to use. Computerized systems layered onto patient care were meant to free doctors from unnecessary work. Unfortunately, they too often add administrative burdens that reduce the effectiveness of patient-doctor interaction instead of increasing it. Some doctors report that they are spending as much as half their time trying to coordinate unconnected health solutions.

Despite that, however, there are already successful AI-driven systems in use meeting a variety of healthcare needs in areas including pharmaceutical drug discovery, diagnosis of illnesses, and hospital care.

Pharmaceutical Drug Discovery

Drug discovery is one of the more significant forms of research currently being conducted ...

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