Jack Dunn
Jack Dunn
Co-Founder, Interpretable AI
Verified email at - Homepage
Cited by
Cited by
Optimal classification trees
D Bertsimas, J Dunn
Machine Learning 106, 1039-1082, 2017
Surgical risk is not linear: derivation and validation of a novel, user-friendly, and machine-learning-based predictive optimal trees in emergency surgery risk (POTTER) calculator
D Bertsimas, J Dunn, GC Velmahos, HMA Kaafarani
Annals of surgery 268 (4), 574-583, 2018
Machine learning under a modern optimization lens
D Bertsimas, J Dunn
Dynamic Ideas LLC, 2019
Robust classification
D Bertsimas, J Dunn, C Pawlowski, YD Zhuo
INFORMS Journal on Optimization 1 (1), 2-34, 2019
Optimal prescriptive trees
D Bertsimas, J Dunn, N Mundru
INFORMS Journal on Optimization 1 (2), 164-183, 2019
Optimal trees for prediction and prescription
JW Dunn
Massachusetts Institute of Technology, 2018
Applied informatics decision support tool for mortality predictions in patients with cancer
D Bertsimas, J Dunn, C Pawlowski, J Silberholz, A Weinstein, YD Zhuo, ...
JCO clinical cancer informatics 2, 1-11, 2018
Validation of the artificial intelligence-based predictive optimal trees in emergency surgery risk (POTTER) calculator in emergency general surgery and emergency laparotomy …
MW El Hechi, LR Maurer, J Levine, D Zhuo, M El Moheb, GC Velmahos, ...
Journal of the American College of Surgeons 232 (6), 912-919. e1, 2021
Trauma outcome predictor: an artificial intelligence interactive smartphone tool to predict outcomes in trauma patients
LR Maurer, D Bertsimas, HT Bouardi, M El Hechi, M El Moheb, ...
Journal of Trauma and Acute Care Surgery 91 (1), 93-99, 2021
Comparison of machine learning optimal classification trees with the pediatric emergency care applied research network head trauma decision rules
D Bertsimas, J Dunn, DW Steele, TA Trikalinos, Y Wang
JAMA pediatrics 173 (7), 648-656, 2019
Optimal policy trees
M Amram, J Dunn, YD Zhuo
Machine Learning 111 (7), 2741-2768, 2022
Adverse outcomes prediction for congenital heart surgery: a machine learning approach
D Bertsimas, D Zhuo, J Dunn, J Levine, E Zuccarelli, N Smyrnakis, ...
World Journal for Pediatric and Congenital Heart Surgery 12 (4), 453-460, 2021
Optimal survival trees
D Bertsimas, J Dunn, E Gibson, A Orfanoudaki
Machine learning 111 (8), 2951-3023, 2022
Near-optimal nonlinear regression trees
D Bertsimas, J Dunn, Y Wang
Operations Research Letters 49 (2), 201-206, 2021
Validation of the Al-based predictive opTimal trees in emergency surgery risk (POTTER) calculator in patients 65 years and older
LR Maurer, P Chetlur, D Zhuo, M El Hechi, GC Velmahos, J Dunn, ...
Annals of Surgery 277 (1), e8-e15, 2023
Comparing interpretability and explainability for feature selection
J Dunn, L Mingardi, YD Zhuo
arXiv preprint arXiv:2105.05328, 2021
Targeted workup after initial febrile urinary tract infection: using a novel machine learning model to identify children most likely to benefit from voiding cystourethrogram
Advanced Analytics Group of Pediatric Urology and ORC Personalized Medicine ...
The Journal of Urology 202 (1), 144-152, 2019
Interpretable predictive maintenance for hard drives
M Amram, J Dunn, JJ Toledano, YD Zhuo
Machine Learning with Applications 5, 100042, 2021
Regression and classification using optimal decision trees
D Bertsimas, J Dunn, A Paschalidis
2017 IEEE MIT undergraduate research technology conference (URTC), 1-4, 2017
Validation of the artificial intelligence–based trauma outcomes predictor (TOP) in patients 65 years and older
M El Hechi, A Gebran, HT Bouardi, LR Maurer, M El Moheb, D Zhuo, ...
Surgery 171 (6), 1687-1694, 2022
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