David S. Restrepo

According to our database, David S. Restrepo authored at least 22 papers between 2022 and 2026.

Collaborative distances:

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

2026

CURENet: combining unified representations for efficient chronic disease prediction.

Cong-Tinh Dao, Nguyen-Minh-Thao Phan, Jun-En Ding, Chenwei Wu, David S. Restrepo, Dongsheng Luo, Fanyi Zhao, Chun-Chieh Liao, Wen-Chih Peng, Chi-Te Wang, Pei-Fu Chen, Ling Chen, Xinglong Ju, Feng Liu, Fang-Ming Hung

Health Inf. Sci. Syst., December, 2026

Medical Context Distorts Decisions in Clinical Vision Language Models.

David S. Restrepo, Sofia Ira Ktena, Maria Vakalopoulou, Stergios Christodoulidis, Enzo Ferrante

CoRR, May, 2026

On the Cone Effect and Modality Gap in Medical Vision-Language Embeddings.

David S. Restrepo, Miguel L. Martins, Chenwei Wu, Luis Filipe Nakayama, Diego M. Lopez, Stergios Christodoulidis, Maria Vakalopoulou, Enzo Ferrante

CoRR, March, 2026

Learning Representations from Incomplete EHR Data with Dual-Masked Autoencoding.

Xiao Xiang, David S. Restrepo, Hyewon Jeong, Yugang Jia, Leo Anthony Celi

CoRR, February, 2026

Implicit Bias in LLMs for Transgender Populations.

Micaela Hirsch, Marina Elichiry, Blas Radi, Tamara Quiroga, David S. Restrepo, Luciana Benotti, Verónica Xhardez, Jocelyn Dunstan, Enzo Ferrante

CoRR, February, 2026

2025

Coefficient of Variation Masking: A Volatility-Aware Strategy for EHR Foundation Models.

Rajna Fani, Rafi Al Attrach, David S. Restrepo, Yugang Jia, Leo Anthony Celi, Peter Schüffler

CoRR, December, 2025

CURENet: Combining Unified Representations for Efficient Chronic Disease Prediction.

Cong-Tinh Dao, Nguyen Minh Thao Phan, Jun-En Ding, Chenwei Wu, David S. Restrepo, Dongsheng Luo, Fanyi Zhao, Chun-Chieh Liao, Wen-Chih Peng, Chi-Te Wang, Pei-Fu Chen, Ling Chen, Xinglong Ju, Feng Liu, Fang-Ming Hung

CoRR, November, 2025

Performance Gains of LLMs With Humans in a World of LLMs Versus Humans.

Lucas McCullum, Pelagie Ami Agassi, Leo Anthony Celi, Daniel K. Ebner, Chrystinne Oliveira Fernandes, Rachel S. Hicklen, Mkliwa Koumbia, Lisa Soleymani Lehmann, David S. Restrepo

CoRR, May, 2025

Representation Learning of Lab Values via Masked AutoEncoder.

David S. Restrepo, Chenwei Wu, Yueran Jia, Jaden K. Sun, Jack Gallifant, Catherine G. Bielick, Yugang Jia, Leo A. Celi

CoRR, January, 2025

Enhancing AI-based diabetic retinopathy screening in low- and middle-income countries with synthetic data.

Zitao Shuai, Chenwei Wu, Zhengxu Tang, David S. Restrepo, Michael G. Morley, Luis Filipe Nakayama

J. Biomed. Informatics, 2025

WorldMedQA-V: a multilingual, multimodal medical examination dataset for multimodal language models evaluation.

João Matos, Shan Chen, Siena Placino, Yingya Li, Juan Carlos Climent Pardo, Daphna Idan, Takeshi Tohyama, David S. Restrepo, Luis Filipe Nakayama, Jose M. M. Pascual-Leone, Guergana K. Savova, Hugo J. W. L. Aerts, Leo Anthony Celi, An-Kwok Ian Wong, Danielle S. Bitterman, Jack Gallifant

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025

Fairness and Robustness of CLIP-Based Models for Chest X-Rays.

Théo Sourget, David S. Restrepo, Céline Hudelot, Enzo Ferrante, Stergios Christodoulidis, Maria Vakalopoulou

Proceedings of the Fairness of AI in Medical Imaging - Third International Workshop, 2025

On the Risk of Misleading Reports: Diagnosing Textual Biases in Multimodal Clinical AI.

David S. Restrepo, Sofia Ira Ktena, Maria Vakalopoulou, Stergios Christodoulidis, Enzo Ferrante

Proceedings of the AI for Clinical Applications - First International Workshops, 2025

Multi-OphthaLingua: A Multilingual Benchmark for Assessing and Debiasing LLM Ophthalmological QA in LMICs.

David S. Restrepo, Chenwei Wu, Zhengxu Tang, Zitao Shuai, Thao Nguyen Minh Phan, Jun-En Ding, Cong-Tinh Dao, Jack Gallifant, Robyn Gayle Dychiao, Jose Carlo Artiaga, André Hiroshi Bando, Carolina Pelegrini Barbosa Gracitelli, Vincenz Ferrer, Leo Anthony Celi, Danielle S. Bitterman, Michael G. Morley, Luis Filipe Nakayama

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Analyzing Diversity in Healthcare LLM Research: A Scientometric Perspective.

David S. Restrepo, Chenwei Wu, Constanza Vásquez-Venegas, João Matos, Jack Gallifant, Luis Filipe

CoRR, 2024

Multimodal Deep Learning for Low-Resource Settings: A Vector Embedding Alignment Approach for Healthcare Applications.

David S. Restrepo, Chenwei Wu, Sebastián Andrés Cajas, Luis Filipe Nakayama, Leo Anthony Celi, Diego M. López

CoRR, 2024

DF-DM: A foundational process model for multimodal data fusion in the artificial intelligence era.

David S. Restrepo, Chenwei Wu, Constanza Vásquez-Venegas, Luis Filipe Nakayama, Leo Anthony Celi, Diego M. López

CoRR, 2024

DengueNet: Dengue Prediction using Spatiotemporal Satellite Imagery for Resource-Limited Countries.

Kuan-Ting Kuo, Dana Moukheiber, Sebastián Cajas Ordonez, David S. Restrepo, Atika Rahman Paddo, Tsung-Yu Chen, Lama Moukheiber, Mira Moukheiber, Sulaiman Moukheiber, Saptarshi Purkayastha, Po-Chih Kuo, Leo Anthony Celi

CoRR, 2024

Efficient In-Context Medical Segmentation with Meta-Driven Visual Prompt Selection.

Chenwei Wu, David S. Restrepo, Zitao Shuai, Zhongming Liu, Liyue Shen

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Seeing Beyond Borders: Evaluating LLMs in Multilingual Ophthalmological Question Answering.

David S. Restrepo, Luis Filipe Nakayama, Robyn Gayle Dychiao, Chenwei Wu, Liam G. McCoy, Jose Carlo Artiaga, Marisa Cobanaj, João Matos, Jack Gallifant, Danielle S. Bitterman, Vincenz Ferrer, Yindalon Aphinyanaphongs, Leo Anthony Celi

Proceedings of the 12th IEEE International Conference on Healthcare Informatics, 2024

MEDFuse: Multimodal EHR Data Fusion with Masked Lab-Test Modeling and Large Language Models.

Phan Nguyen Minh Thao, Cong-Tinh Dao, Chenwei Wu, Jian-Zhe Wang, Shun Liu, Jun-En Ding, David S. Restrepo, Feng Liu, Fang-Ming Hung, Wen-Chih Peng

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2022

Risk Factors for COVID-19: A Systematic Mapping Study.

Paula A. Rosero, Juan S. Realpe, Charic D. Farinango, David S. Restrepo, Ricardo Salazar Cabrera, Diego M. Lopez

Proceedings of the pHealth 2022 - Proceedings of the 19th International Conference on Wearable Micro and Nano Technologies for Personalized Health, 2022