Artificial intelligence is starting to play a transformational role in the healthcare industry, even if opportunities for using it are just beginning to be explored.
That’s an initial finding of a new report from JASON, an independent group of scientists advising the federal government on science and technology issues. The Department of Health and Human Services and the Robert Wood Johnson Foundation commissioned the report; the names of the scientists who developed the report are not being released.
Computers can match human competence in image recognition and, in some studies, can make diagnostic decisions on medical images that match or exceed the ability of clinicians. Technology is also getting better at speech recognition and natural language processing.
However, while the healthcare industry has a huge amount of data, the quality and accessibility to pertinent data at an affordable cost remains a challenge, as does the protection and sharing of data.
“Further, the lack of interoperability of electronic health record systems impedes even the simplest of computational methods and the inability to capture relevant social and environmental information in existing systems leaves a key set of variables out of data streams for individual health,” the scientists wrote.
Yet, such cautions are not slowing the work being done on healthcare artificial intelligence; the report found that 106 start-up companies are already transforming the industry. Three forces currently driving the use of artificial intelligence:
• Frustration with legacy medical systems.
• The ubiquity of networked smart devices in society.
• Acclimation to convenience and at-home services such as those provided by Amazon and other companies.
Study authors are particularly optimistic about two uses of AI to support medical imaging: detection of diabetic retinopathy in retinal fundus images and dermatological classification of skin cancer.
Another area of promise is the proliferation of personal devices such as smartphones and professional medical devices, along with apps to support AI projects.
“There are many impressive smartphone attachments and apps currently available for monitoring of personal health,” according to the JASON report. “These devices empower individuals to monitor and understand their own health, create large corpuses of data that can, in theory, be used for AI applications, and capture health data that can be shared with clinicians and researchers. AI algorithms drive the performance of many of these devices and, reciprocally, these devices are capturing data that could be used to develop or improve AI algorithms.”
Examples of such apps include a personal EKG to detect atrial fibrillation, an app called CloudUPDRS to assess Parkinson’s symptoms including tremors, patterns in gait and a finger-tapping test; and asthma tracking and control via a hand-held flow meter.
“These sorts of technologies can collect information of clear and vital importance to patients and use by clinicians, but we must again emphasize that each new data stream must be evaluated, collected and curated to formats consistent with clinical needs and AI applications,” the scientists caution.
The full 70-page report, “Artificial Intelligence for Health and Health Care,” including findings and recommendations, is available here.
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