Leigh Anne Tang, a PhD student in the lab, led a new study now out in JMIR Public Health and Surveillance based on her work as an analyst with incredible collaborators at the Tennessee Department of Health. Read the full study here; the abstract is below. Background: Fatal drug overdose surveillance informs prevention but is…
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New Paper – Integration of Face-to-Face Screening With Real-time Machine Learning to Predict Risk of Suicide Among Adults
A new study led by Drew Wilimitis, statistical analyst in the lab, is out now in JAMA Network Open. Co-authors include our wonderful collaborators Robert Turer, MD, MS; Michael Ripperger; Allison McCoy, PhD; Sarah Sperry, PhD; Elliot Fielstein, PhD; and Troy Kurz, MD. In this study, we asked: what happens when we combine automated risk…
New Paper – Risky business: a scoping review for communicating results of predictive models between providers and patients
Given widespread excitement around predictive analytics and the proliferation of machine learning algorithms that predict outcomes, a key next step is understanding how this information is — or should be — communicated with patients. In collaboration with Mollie McKillop, Patricia Lee, Joyce Harris, Christopher Simpson, and Laurie Novak, we conducted a scoping review to identify…
Walsh Science 