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Garbage in, Garbage out-Words of Caution on Big Data and Machine Learning in Medical Practice

Garbage in, Garbage out-Words of Caution on Big Data and Machine Learning in Medical Practice

Big data are here. Increasingly, health care professionals will make clinical decisions using prediction rules based on large data sets that use artificial intelligence or machine learning. For example, machine learning and data mining have been used in large administrative databases to predict numerous outcomes, including which patients are at risk for adverse events from opiates. A recent article1 used a Canadian medication prescribing database involving 853 324 participants to predict 30-day opioid-related adverse events. The reported C statistic of 0.82 indicated good discrimination. In addition, the key finding was that the top 0.1 percentile of estimated risk had a positive likelihood ratio of 28.1—this translates to a posttest probability of 43.1%. The question now is whether or how these types of findings should be used not only in opioid prescribing, but other clinical matters as well.

Publication Date: 2023

ISBN: 2689-0186

File Type: 0397
Tags: Healthcare
Author: Joan M Teno
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