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A patient goes into the emergency room for a broken toe, is given a series of standardized tests, has their data fed into an algorithm, and—though they haven’t mentioned feeling depressed or having any suicidal thoughts—the machine identifies them as at high risk of suicide in the next week. Though the patient didn’t ask for help, medical professionals must now broach the subject of suicide and find some way of intervening. This scenario, where an actionable diagnosis comes not from a doctor’s evaluation or family member’s concern, but an algorithm, is an imminent reality.

A new study has sought to address the challenges of the kidney exchange program and introduced the concept of "failure-aware" algorithmic matching to improve success rates. The study, "Failure-Aware Kidney Exchange," was conducted by John Dickerson of the University of Maryland, and Ariel Procaccia and Tuomas Sandholm of Carnegie Mellon University, and published in the INFORMS journal Management Science.

Cornell researchers' work to improve bike share programs continues to make new innovations, to include recognition as a finalist for the 2018 INFORMS Wagner Prize for Excellence in Operations Research Practice.