Predicting Outcomes of Septic Shock Patients Using Feature Selection Based on Soft Computing Techniques. - André S. Fialho; Federico Cismondi; Susana M. Vieira; João Miguel da Costa Sousa; Shane R. Reti; Michael D. Howell; Stan N. Finkelstein (IPMU (2), 2010)

Computational intelligence methods for processing misaligned, unevenly sampled time series containing missing data. - Federico Cismondi; André S. Fialho; Susana M. Vieira; João M. C. Sousa; Shane R. Reti; Michael D. Howell; Stan N. Finkelstein (CIDM, 2011)

Predicting laboratory testing in intensive care using fuzzy and neural modeling. - Federico Cismondi; André S. Fialho; Susana M. Vieira; João M. C. Sousa; Shane R. Reti; Leo A. Celi; Michael D. Howell; Stan N. Finkelstein (FUZZ-IEEE, 2011)

Fuzzy modeling to predict administration of vasopressors in intensive care unit patients. - André S. Fialho; Federico Cismondi; Susana M. Vieira; João M. C. Sousa; Shane R. Reti; Leo A. Celi; Michael D. Howell; Stan N. Finkelstein (FUZZ-IEEE, 2011)

Predicting septic shock outcomes in a database with missing data using fuzzy modeling: Influence of pre-processing techniques on real-world data-based classification. - Ruben D. M. A. Pereira; André S. Fialho; Federico Cismondi; Susana M. Vieira; João M. C. Sousa; Rui Jorge Almeida; Uzay Kaymak; Shane R. Reti; Michael D. Howell; Stan N. Finkelstein (FUZZ-IEEE, 2011)

Network Analysis of Digital Crumbs from an Electronic Health Record: From newborns to adults, ideas to applications. - James E. Gray; Shane R. Reti; Henry J. Feldman; Patricia Folcarelli; Xiaoning Lu; Roger B. Davis; Michael D. Howell; Charles Safran (AMIA, 2012)

A Deeper Exploration of Contagious Risk and the Neighborhood Effect. - Anoop M. Mayampurath; Dana P. Edelson; Michael D. Howell; Matthew M. Churpek; Samuel L. Volchenboum (CRI, 2017)

Scalable and accurate deep learning for electronic health records. - Alvin Rajkomar; Eyal Oren; Kai Chen 010; Andrew M. Dai; Nissan Hajaj; Peter J. Liu; Xiaobing Liu; Mimi Sun; Patrik Sundberg; Hector Yee; Kun Zhang 043; Gavin E. Duggan; et al. (CoRR, 2018)

Scalable and accurate deep learning with electronic health records. - Alvin Rajkomar; Eyal Oren; Kai Chen 010; Andrew M. Dai; Nissan Hajaj; Michaela Hardt; Peter J. Liu; Xiaobing Liu; Jake Marcus; Mimi Sun; Patrik Sundberg; Hector Yee; et al. (npj Digit. Medicine, 2018)

Explaining an increase in predicted risk for clinical alerts. - Michaela Hardt; Alvin Rajkomar; Gerardo Flores; Andrew M. Dai; Michael D. Howell; Greg Corrado; Claire Cui; Moritz Hardt (CHIL, 2020)

Customization scenarios for de-identification of clinical notes. - Tzvika Hartman; Michael D. Howell; Jeff Dean; Shlomo Hoory; Ronit Slyper; Itay Laish; Oren Gilon; Danny Vainstein; Greg Corrado; Katherine Chou; Ming Jack Po; Jutta Williams; et al. (BMC Medical Informatics Decis. Mak., 2020)

Privacy-first health research with federated learning. - Adam Sadilek; Luyang Liu; Dung Nguyen 002; Methun Kamruzzaman; Stylianos Serghiou; Benjamin Rader; Alex Ingerman; Stefan Mellem; Peter Kairouz; Elaine O. Nsoesie; Jamie Macfarlane; Anil Vullikanti; et al. (npj Digit. Medicine, 2021)