Vincent Jeanselme

According to our database, Vincent Jeanselme authored at least 17 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

One Loss to Rule Them All: Marked Time-to-Event for Structured EHR Foundation Models.

Zilin Jing, Vincent Jeanselme, Yuta Kobayashi, Simon A. Lee, Chao Pang, Aparajita Kashyap, Yanwei Li, Xinzhuo Jiang, Shalmali Joshi

CoRR, February, 2026

2025

Mind the data gap: Missingness Still Shapes Large Language Model Prognoses.

Yuta Kobayashi, Vincent Jeanselme, Shalmali Joshi

CoRR, December, 2025

Reflections from Research Roundtables at the Conference on Health, Inference, and Learning (CHIL) 2025.

Emily Alsentzer, Marie-Laure Charpignon, Bill Chen, Niharika D'Souza, Jason A. Fries, Yixing Jiang, Aparajita Kashyap, Chanwoo Kim, Simon A. Lee, Aishwarya Mandyam, Ashery Christopher Mbilinyi, Nikita Mehandru, Nitish Nagesh, Brighton Nuwagira, Emma Pierson, Arvind Pillai, Akane Sano, Tanveer F. Syeda-Mahmood, Shashank Yadav, Elias Adhanom, Muhammad Umar Afza, Amelia Archer, Suhana Bedi, Vasiliki Bikia, Trenton Chang, George H. Chen, Winston Chen, Erica Chiang, Edward Choi, Octavia Ciora, Paz Dozie-Nnamah, Shaza Elsharief, Matthew Engelhard, Ali Eshragh, Jean Feng, Josh Fessel, Scott L. Fleming, Kei Sen Fong, Thomas Frost, Soham Gadgil, Judy Gichoya, Leeor Hershkovich, Sujeong Im, Bhavya Jain, Vincent Jeanselme, Furong Jia, Qixuan Jin, Yuxuan Jin, Daniel Kapash, Geetika Kapoor, Behdokht Kiafar, Matthias Kleiner, Stefan Kraft, Annika Kumar, Daeun Kyung, Zhongyuan Liang, Joanna Lin, Qianchu Liu, Chang Liu, Hongzhou Luan, Chris Lunt, Leopoldo Julian Lechuga López, Matthew B. A. McDermott, Shahriar Noroozizadeh, Connor O'Brien, YongKyung Oh, Mixail Ota, Stephen Pfohl, Meagan Pi, Tanmoy Sarkar Pias, Emma Rocheteau, Avishaan Sethi, Toru Shirakawa, Anita Silver, Neha Simha, Kamile Stankeviciute, Max Sunog, Peter Szolovits, Shengpu Tang, Jialu Tang, Aaron Tierney, John Valdovinos, Byron Wallace, Will Ke Wang, Peter Washington, Jeremy C. Weiss, Daniel Wolfe, Emily Wong, Hye Sun Yun, Xiaoman Zhang, Xiao Yu Cindy Zhang, Hayoung Jeong, Kaveri A. Thakoor

CoRR, October, 2025

Prediction of Survival Outcomes under Clinical Presence Shift: A Joint Neural Network Architecture.

Vincent Jeanselme, Glen P. Martin, Matthew Sperrin, Niels Peek, Brian D. M. Tom, Jessica K. Barrett

CoRR, August, 2025

Competing Risks: Impact on Risk Estimation and Algorithmic Fairness.

Vincent Jeanselme, Brian D. M. Tom, Jessica K. Barrett

CoRR, August, 2025

ICYM2I: The illusion of multimodal informativeness under missingness.

Young Sang Choi, Vincent Jeanselme, Pierre A. Elias, Shalmali Joshi

CoRR, May, 2025

FoMoH: A clinically meaningful foundation model evaluation for structured electronic health records.

Chao Pang, Vincent Jeanselme, Young Sang Choi, Xinzhuo Jiang, Zilin Jing, Aparajita Kashyap, Yuta Kobayashi, Yanwei Li, Florent Pollet, Karthik Natarajan, Shalmali Joshi

CoRR, May, 2025

Leveraging Expert Consistency to Improve Algorithmic Decision Support.

Maria De-Arteaga, Vincent Jeanselme, Artur Dubrawski, Alexandra Chouldechova

Manag. Sci., 2025

ADHAM: Additive Deep Hazard Analysis Mixtures for Interpretable Survival Regression.

Mert Ketenci, Vincent Jeanselme, Harry Reyes Nieva, Shalmali Joshi, Noémie Elhadad

Proceedings of the Machine Learning for Healthcare Conference (MLHC 2025), 2025

2024

Constrained clustering and multiple kernel learning without pairwise constraint relaxation.

Benedikt Boecking, Vincent Jeanselme, Artur Dubrawski

Adv. Data Anal. Classif., June, 2024

Identifying treatment response subgroups in observational time-to-event data.

Vincent Jeanselme, Chang Ho Yoon, Fabian Falck, Brian D. M. Tom, Jessica K. Barrett

CoRR, 2024

Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium.

Hyewon Jeong, Sarah Jabbour, Yuzhe Yang, Rahul Thapa, Hussein Mozannar, William Jongwon Han, Nikita Mehandru, Michael Wornow, Vladislav Lialin, Xin Liu, Alejandro Lozano, Jiacheng Zhu, Rafal Dariusz Kocielnik, Keith Harrigian, Haoran Zhang, Edward Lee, Milos Vukadinovic, Aparna Balagopalan, Vincent Jeanselme, Katherine Matton, Ilker Demirel, Jason A. Fries, Parisa Rashidi, Brett K. Beaulieu-Jones, Xuhai Orson Xu, Matthew B. A. McDermott, Tristan Naumann, Monica Agrawal, Marinka Zitnik, Berk Ustun, Edward Choi, Kristen Yeom, Gamze Gürsoy, Marzyeh Ghassemi, Emma Pierson, George H. Chen, Sanjat Kanjilal, Michael Oberst, Linying Zhang, Harvineet Singh, Tom Hartvigsen, Helen Zhou, Chinasa T. Okolo

CoRR, 2024

2023

Neural Fine-Gray: Monotonic neural networks for competing risks.

Vincent Jeanselme, Chang Ho Yoon, Brian D. M. Tom, Jessica K. Barrett

Proceedings of the Conference on Health, Inference, and Learning, 2023

2022

DeepJoint: Robust Survival Modelling Under Clinical Presence Shift.

Vincent Jeanselme, Glen P. Martin, Niels Peek, Matthew Sperrin, Brian D. M. Tom, Jessica K. Barrett

CoRR, 2022

Imputation Strategies Under Clinical Presence: Impact on Algorithmic Fairness.

Vincent Jeanselme, Maria De-Arteaga, Zhe Zhang, Jessica K. Barrett, Brian D. M. Tom

Proceedings of the Machine Learning for Health, 2022

Neural Survival Clustering: Non-parametric mixture of neural networks for survival clustering.

Vincent Jeanselme, Brian D. M. Tom, Jessica K. Barrett

Proceedings of the Conference on Health, Inference, and Learning, 2022

2021

Deep Parametric Time-to-Event Regression with Time-Varying Covariates.

Chirag Nagpal, Vincent Jeanselme, Artur Dubrawski

Proceedings of AAAI Symposium on Survival Prediction, 2021