The Rise and Rise of Quantitative Cassandras

By SAURABH JHA, MD

Despite an area under the ROC curve of 1, Cassandra’s
prophesies were never believed. She neither hedged nor relied on retrospective
data – her predictions, such as the Trojan war, were prospectively validated. In
medicine, a new type of Cassandra has emerged – 
one who speaks in probabilistic tongue, forked unevenly between the
probability of being right and the possibility of being wrong. One who, by conceding
that she may be categorically wrong, is technically never wrong. We call these
new Minervas “predictions.” The Owl of Minerva flies above its denominator.

Deep learning (DL) promises to transform the prediction
industry from a stepping stone for academic promotion and tenure to something
vaguely useful for clinicians at the patient’s bedside. Economists studying AI believe that AI is revolutionary,
revolutionary like the steam engine and the internet, because it better predicts.

Recently published in Nature, a sophisticated DL algorithm was able to predict acute kidney injury (AKI), continuously, in hospitalized patients by extracting data from their electronic health records (EHRs). The algorithm interrogated nearly million EHRS of patients in Veteran Affairs hospitals. As intriguing as their methodology is, it’s less interesting than their results. For every correct prediction of AKI, there were two false positives. The false alarms would have made Cassandra blush, but they’re not bad for prognostic medicine. The DL...

Source: The Health Care Blog - October 7, 2019 Category: Consumer Health News Authors: Christina Liu Tags: Artificial Intelligence Data Medical Practice Physicians RogueRad @roguerad acute kidney injury AI deep learning machine learning predictions Saurabh Jha Source Type: blogs