[Skip to Content]
Access to paid content on this site is currently suspended due to excessive activity being detected from your IP address 34.204.191.0. Please contact the publisher to request reinstatement.
[Skip to Content Landing]
Viewpoint
November 22, 2019

Machine Learning, Predictive Analytics, and Clinical Practice: Can the Past Inform the Present?

Author Affiliations
  • 1Duke University Medical Center, Durham, North Carolina
  • 2Associate Editor, JAMA
JAMA. 2019;322(23):2283-2284. doi:10.1001/jama.2019.17831

Physicians’ minds, no matter how bright or experienced, are fallible—unable to adequately store, recall, and correctly analyze the millions of pieces of medical information needed to optimally care for patients. The promise of machine learning (ML) and predictive analytics is that clinicians’ decisions can be augmented by computers rather than relying solely on their brains. For example, automated ML algorithms can rapidly search through gigabytes of data and generate probabilistic estimates of patients’ likelihood for different outcomes, such as various disease complications or death. With these empirical estimates, patients and their physicians could make better informed care decisions.

Limit 200 characters
Limit 25 characters
Conflicts of Interest Disclosure

Identify all potential conflicts of interest that might be relevant to your comment.

Conflicts of interest comprise financial interests, activities, and relationships within the past 3 years including but not limited to employment, affiliation, grants or funding, consultancies, honoraria or payment, speaker's bureaus, stock ownership or options, expert testimony, royalties, donation of medical equipment, or patents planned, pending, or issued.

Err on the side of full disclosure.

If you have no conflicts of interest, check "No potential conflicts of interest" in the box below. The information will be posted with your response.

Not all submitted comments are published. Please see our commenting policy for details.

Limit 140 characters
Limit 3600 characters or approximately 600 words
    ×