Law360 (October 24, 2019, 1:21 PM EDT) — On Oct. 10, a National Institutes of Health team, led by Ian Hutchins, published its exciting new work, “Predicting Translational Progress in Biomedical Research.” The team built a machine learning system that detects whether a paper and its underlying research are likely to be clinically successful, i.e., lead to commercial products for human use.
Specifically, the team created an artificial intelligence-based, big-data model that evaluates research papers based on multiple metrics to determine if that particular study or innovation is likely to lead to “transformative clinical impact.” That likelihood of success is expressed as “approximate potential to translate.”
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