Multi-task deep learning-based survival analysis on the prognosis of late AMD using the longitudinal data in AREDS. - Gregory C. Ghahramani; Matthew Brendel; Mingquan Lin; Qingyu Chen 001; Tiarnan D. Keenan; Kun Chen 002; Emily Y. Chew; Zhiyong Lu; Yifan Peng 002; Fei Wang 001 (AMIA, 2021)

Comprehensively modeling heterogeneous symptom progression for Parkinson's disease subtyping. - Chang Su 002; Yu Hou; Jielin Xu; Matthew Brendel; Jacqueline R. M. A. Maasch; Zilong Bai; Yingying Zhu 003; Claire Henchcliffe; Feixiong Cheng; Fei Wang 001 (AMIA, 2022)

Improving Cell Type Classification in Histology Images with Active Learning. - Justin Xiang; Richard Bell; Matthew Brendel; Edward Schwarz; Fei Wang 001 (AMIA, 2022)

Application of Deep Learning on Single-cell RNA Sequencing Data Analysis: A Review. - Matthew Brendel; Chang Su 002; Zilong Bai; Hao Zhang 050; Olivier Elemento; Fei Wang 001 (Genom. Proteom. Bioinform., 2022)

Identification of Parkinson's disease PACE subtypes and repurposing treatments through integrative analyses of multimodal data. - Chang Su 002; Yu Hou; Jielin Xu; Zhenxing Xu; Manqi Zhou; Alison Ke; Haoyang Li 001; Jie Xu 012; Matthew Brendel; Jacqueline R. M. A. Maasch; Zilong Bai; Haotan Zhang; et al. (npj Digit. Medicine, 2024)

Predicting response to neoadjuvant chemotherapy in muscle-invasive bladder cancer via interpretable multimodal deep learning. - Zilong Bai; Mohamed Osman; Matthew Brendel; Catherine M. Tangen; Thomas W. Flaig; Ian M. Thompson; Melissa Plets; M. Scott Lucia; Dan Theodorescu; Daniel Gustafson; Siamak Daneshmand; Joshua J. Meeks; et al. (npj Digit. Medicine, 2025)