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Healthcare Artificial Intelligence Making Sense of Data Flood

Healthcare artificial intelligence and machine learning are providing tools to enable medical practitioners and researchers to make sense of the flood of medical data.

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Source: Thinkstock

By Fred Donovan

- Healthcare artificial intelligence (AI) and machine learning are providing tools to enable medical practitioners and researchers to make sense of the flood of medical data, according to study by Stanford Medicine.

AI and other technical innovations are helping ensure data is appropriately cleaned, managed, and shared in the healthcare ecosystem.

“Many roadblocks and inefficiencies that have encumbered this digital transition are gradually being phased out and eliminated,” the noted report, The Democratization of Health Care.

The report cited an Accenture analysis predicting that the market for healthcare AI would increase at a CAGR of 40 percent and would reach $6.6 billion in 2021.

Accenture identified the following healthcare AI applications that are expected to generate the most annual benefit by 2026: robot-assisted surgery ($40 billion), virtual nursing assistance ($20 billion), administrative workflow assistance ($19 billion), fraud detection ($17 billion), dosage error reduction ($16 billion), connected machines ($14 billion), clinical trial participant identifier ($13 billion), preliminary diagnosis ($5 billion), automated image diagnosis ($3 billion), and cybersecurity ($2 billion).

AI algorithms have become highly sophisticated. For example, image recognition algorithms can quickly process hundreds of thousands of medical images.  

In fact, a Stanford-developed AI algorithm for radiology can reliably screen chest x-rays for more than a dozen types of disease in seconds, the report noted.

“[In] the next 2 to 5 years there will be a lot of attention on data analytics and artificial intelligence that will allow us to learn from large observational datasets. It will teach us what we do today which we don’t understand, how varied our practices are, and what outcomes we get with them,” Paul Tan, vice president and chief health transformation officer at IBM Watson Health, was quoted as saying in the report.  

The Stanford report identified a number of near-term and long-term benefits from artificial intelligence. AI will help healthcare predict and identify public health threats and outcomes for at-risk patients. It will also enable physicians to customer treatment plans and drugs to patients based on factors such as their genetic makeup, habits, and biometrics.

AI could help to facilitate virtual and mobile device care, providing patients access to a healthcare specialists at any time on any device.

It could also help slow the progression of chronic disease at a population level by ensuring that right care takes place at the right time and in the right setting.

AI could help reduce US healthcare costs by $150 billion by 2026. “From a business perspective, intelligent computing creates an opportunity for industry players to optimize savings and profitability while still taking advantage of growth,” the report observed.

The technology could also help with physician burnout by automating clerical tasks that are leading to burnout and fatigue. A recent Stanford Medicine survey found that a majority of physicians were showing signs of burnout, such as exhaustion, cynicism, and reduced effectiveness.

AI can also help radiologists in pinpointing abnormalities such as heart disease and cancer and conducting image-guided procedures and biopsies. The use of algorithms has the potential to significantly improve the accuracy of screening and diagnostics.

“The potential for AI to positively impact our practices and make radiology professionals even more valuable to our patients and health systems is enormous, but to be effective the design and development of these use cases must have substantial input from radiologists,” observed Bibb Allen and Keith Dreyer in the Journal of the American College of Radiology.

At the same time, public opinion is divided on the role of AI in healthcare. More than half of respondents to an Northstar Research Partners and ARM survey would willing to let an AI doctor perform an eye exam, a majority of respondents were not will to have an AI doctor perform brain surgery.

“Intelligent computing and AI should not be viewed as a means of replacing doctors; the human element is an important keystone in the physician-patient relationship,” the report concluded.

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