Aimé, N., Olivier, B., Gaël, G., Frédéric, L., & Ivan, L. (2025). Simsamu-a french medical dispatch dialog open dataset. Computer Methods and Programs in Biomedicine, 108857.
Empana, J.-P., Lerner, I., Perier, M.-C., Guibout, C., Jabre, P., Bailly, K., Andrieu, M., Climie, R., van Sloten, T., Vedie, B., & others. (2022). Ultrasensitive troponin I and incident cardiovascular disease. Arteriosclerosis, Thrombosis, and Vascular Biology, 42(12), 1471–1481.
Empana, J.-P., Lerner, I., Valentin, E., Folke, F., Böttiger, B., Gislason, G., Jonsson, M., Ringh, M., Beganton, F., Bougouin, W., & others. (2022). Incidence of sudden cardiac death in the European Union. Journal of the American College of Cardiology, 79(18), 1818–1827.
Ghebriout, M. I. E., Guibon, G., Lerner, I., & Vincent, E. (2025). QUARTZ: QA-based Unsupervised Abstractive Refinement for Task-oriented Dialogue Summarization. ArXiv Preprint ArXiv:2509.26302.
Jouffroy, J., Feldman, S. F., Lerner, I., Rance, B., Burgun, A., Neuraz, A., & others. (2021). Hybrid deep learning for medication-related information extraction from clinical texts in French: MedExt algorithm development study. JMIR Medical Informatics, 9(3), e17934.
Jouffroy, J., Feldman, S. F., Lerner, I., Rance, B., Neuraz, A., & Burgun, A. (2020). MedExt: combining expert knowledge and deep learning for medication extraction from French clinical texts. Published Online January, 23.
Kalimouttou, A., Lerner, I., Cheurfa, C., Jannot, A.-S., & Pirracchio, R. (2023). Machine-learning-derived sepsis bundle of care. Intensive Care Medicine, 49(1), 26–36.
Lerner, I. (2024). Sur la conception et l’apprentissage de structures invariantes dans les modèles de séries temporelles cliniques [Phdthesis]. Université Paris Cite.
Lerner, I., Burgun, A., & Bach, F. (2025). Spectral structure learning for clinical time series. ArXiv Preprint ArXiv:2502.11680.
Lerner, I., Chariot, P., Lefèvre, T., & others. (2024). Functional Impairment in Individuals Exposed to Violence Based on Electronical Forensic Medical Record Mining and Their Profile Identification: Controlled Observational Study. JMIR Public Health and Surveillance, 10(1), e43563.
Lerner, I., Créquit, P., Ravaud, P., & Atal, I. (2019). Automatic screening using word embeddings achieved high sensitivity and workload reduction for updating living network meta-analyses. Journal of Clinical Epidemiology, 108, 86–94.
Lerner, I., Jouffroy, J., Burgun, A., & Neuraz, A. (2020). Learning the grammar of drug prescription: recurrent neural network grammars for medication information extraction in clinical texts. ArXiv Preprint ArXiv:2004.11622.
Lerner, I., Paris, N., & Tannier, X. (2020). Terminologies augmented recurrent neural network model for clinical named entity recognition. Journal of Biomedical Informatics, 102, 103356.
Lerner, I., Serret-Larmande, A., Rance, B., Garcelon, N., Burgun, A., Chouchana, L., & Neuraz, A. (2022). Mining Electronic Health Records for Drugs Associated With 28-day Mortality in COVID-19: Pharmacopoeia-wide Association Study (PharmWAS). JMIR Medical Informatics, 10(3), e35190.
Lerner, I., Veil, R., Nguyen, D.-P., Luu, V. P., & Jantzen, R. (2018). Revolution in health care: How will data science impact doctor–patient relationships? Frontiers in Public Health, 6, 99.
Neuraz, A., Lerner, I., Digan, W., & Paris, N. (2020). Rosy Tsopra, Alice Rogier, David Baudoin, Kevin Bretonnel Cohen, Anita Burgun, Nicolas Garcelon, et al. 2020. Natural language processing for rapid response to emergent diseases: Case study of calcium channel blockers and hypertension in the COVID-19 pandemic. Journal of Medical Internet Research, 22(8), e20773.
Neuraz, A., Lerner, I., Digan, W., Paris, N., Tsopra, R., Rogier, A., Baudoin, D., Cohen, K. B., Burgun, A., Garcelon, N., & others. (2020a). Natural language processing for rapid response to emergent diseases: case study of calcium channel blockers and hypertension in the COVID-19 pandemic. Journal of Medical Internet Research, 22(8), e20773.
Neuraz, A., Lerner, I., Digan, W., Paris, N., Tsopra, R., Rogier, A., Baudoin, D., Cohen, K., Burgun, A., Garcelon, N., & others. (2020b). AP-HP/Universities/INSERM COVID-19 Research Collaboration; AP-HP COVID CDR Initiative. Natural language processing for rapid response to emergent diseases: case study of calcium channel blockers and hypertension in the COVID-19 pandemic. J Med Internet Res, 22(8), e20773.
Vincent, M., Douillet, M., Lerner, I., Neuraz, A., Burgun, A., & Garcelon, N. (2022). Using deep learning to improve phenotyping from clinical reports. In MEDINFO 2021: One World, One Health–Global Partnership for Digital Innovation (pp. 282–286). IOS Press.