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Reduction of Mental Health–Related Emergency Department Admissions for Youth and Young Adults Following a Remote Intensive Outpatient Program: Quality Improvement Analysis

Kate Gliske, Jaime Ballard, Katie R Berry, Michael Killian, Elizabeth Kroll, Caroline Fenkel

JMIR Form Res 2023;7:e47895

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Predicting Youth and Young Adult Treatment Engagement in a Transdiagnostic Remote Intensive Outpatient Program: Latent Profile Analysis

Kate Gliske, Katie R Berry, Jaime Ballard, Clare Schmidt, Elizabeth Kroll, Jonathan Kohlmeier, Michael Killian, Caroline Fenkel

JMIR Form Res 2023;7:e47917

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Prediction of Outcomes After Heart Transplantation in Pediatric Patients Using National Registry Data: Evaluation of Machine Learning Approaches

Killian et al [15] extracted the data of pediatric patients who underwent heart, kidney, or liver transplantation from UNOS data from a single transplant center in the United States and focused on the prediction of hospitalization within the observation windows of 1, 3, and 5 years after each patient’s first organ transplantation using both traditional ML methods (RF, LR, multilayer perceptron [MLP], and support vector machine [SVM]) and a simple feed-forward NN model.

Michael O Killian, Shubo Tian, Aiwen Xing, Dana Hughes, Dipankar Gupta, Xiaoyu Wang, Zhe He