Team
CBIO
Biography
Eloïse Berson is a researcher specializing in the application of artificial intelligence and deep learning methods to translational medicine and systems biology. Her work focuses on multiomic analysis and the integration of clinical data to improve risk stratification, predict clinical outcomes, and understand the mechanisms underlying complex diseases. She has contributed to the development of innovative models, such as tools for deconvolving epigenomic and transcriptomic data (e.g., Cellformer) to identify specific cellular signatures associated with conditions such as Alzheimer’s disease or cognitive resilience. Her research also addresses complications of neonatal prematurity, where she has helped create predictive metabolic indices (e.g., *metabolic health index*) to assess the risks of bronchopulmonary dysplasia or necrotizing enterocolitis, by combining deep learning approaches with neonatal screening data. More recently, her work has explored the impact of psychosocial factors and modifiable interventions on pregnancy outcomes, incorporating cellular immune profiles to guide precision medicine strategies.
Publication(s)
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2026
Quantitative assessment of neonatal health using dried blood spot metabolite profiles and deep learning DOI : 10.1126/scitranslmed.adv4942
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2025
Deep learning-based cell type profiles reveal signatures of Alzheimer's disease resilience and resistance DOI : 10.1093/brain/awaf285
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2025
Epigenomic profile of GBA1 in Parkinson's disease DOI : 10.1016/j.parkreldis.2025.108066
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2025
Mitigation of outcome conflation in predicting patient outcomes using electronic health records DOI : 10.1093/jamia/ocaf033
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2025
Benchmarking of pre-training strategies for electronic health record foundation models DOI : 10.1093/jamiaopen/ooaf090
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2025
Correction to: A machine learning approach to leveraging electronic health records for enhanced omics analysis (Nature Machine Intelligence, (2025), 7, 2, (293-306), 10.1038/s42256-024-00974-9) DOI : 10.1038/s42256-025-01021-x
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2025
Mediterranean vs. Western diet effects on the primate cerebral cortical pre-synaptic proteome: Relationships with the transcriptome and multi-system phenotypes DOI : 10.1002/alz.70041
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2025
Author Correction: AI-guided precision parenteral nutrition for neonatal intensive care units (Nature Medicine, (2025), 31, 6, (1882-1894), 10.1038/s41591-025-03601-1) DOI : 10.1038/s41591-025-03691-x
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2025
AI-guided precision parenteral nutrition for neonatal intensive care units DOI : 10.1038/s41591-025-03601-1
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2025
A machine learning approach to leveraging electronic health records for enhanced omics analysis DOI : 10.1038/s42256-024-00974-9
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2025
Infusion of young donor plasma components in older patients modifies the immune and inflammatory response to surgical tissue injury: a randomized clinical trial DOI : 10.1186/s12967-025-06215-w
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2025
Development and validation of a pre-trained language model for neonatal morbidities: a retrospective, multicentre, prognostic study DOI : 10.1016/j.landig.2025.100926
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2024
Intra- and post-pandemic impact of the COVID-19 outbreak on Stanford Health Care DOI : 10.1016/j.acpath.2024.100113
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2024
Generating pregnant patient biological profiles by deconvoluting clinical records with electronic health record foundation models DOI : 10.1093/bib/bbae574
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2024
Unlocking human immune system complexity through AI DOI : 10.1038/s41592-024-02351-1
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2024
Comprehensive overview of the anesthesiology research landscape: A machine Learning Analysis of 737 NIH-funded anesthesiology primary Investigator's publication trends DOI : 10.1016/j.heliyon.2024.e29050
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2024
Single-cell peripheral immunoprofiling of lewy body and Parkinson’s disease in a multi-site cohort DOI : 10.1186/s13024-024-00748-2
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2023
In-silico generation of high-dimensional immune response data in patients using a deep neural network DOI : 10.1002/cyto.a.24709
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2023
Prediction of neuropathologic lesions from clinical data DOI : 10.1002/alz.12921
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2023
Understanding the molecular basis of resilience to Alzheimer’s disease DOI : 10.3389/fnins.2023.1311157
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2023
Large-scale correlation network construction for unraveling the coordination of complex biological systems DOI : 10.1038/s43588-023-00429-y
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2023
Quantitative estimate of cognitive resilience and its medical and genetic associations DOI : 10.1186/s13195-023-01329-z
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2023
Multiomic signals associated with maternal epidemiological factors contributing to preterm birth in low- and middle-income countries DOI : 10.1126/sciadv.ade7692
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2023
Data-driven longitudinal characterization of neonatal health and morbidity DOI : 10.1126/scitranslmed.adc9854
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2023
Whole genome deconvolution unveils Alzheimer’s resilient epigenetic signature DOI : 10.1038/s41467-023-40611-4
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2023
Cross-species comparative analysis of single presynapses DOI : 10.1038/s41598-023-40683-8
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2023
Deep representation learning identifies associations between physical activity and sleep patterns during pregnancy and prematurity DOI : 10.1038/s41746-023-00911-x
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2022
Revealing the impact of lifestyle stressors on the risk of adverse pregnancy outcomes with multitask machine learning DOI : 10.3389/fped.2022.933266
PhD supervision
- 2025 Biologically interpretable prediction of long-term disease risk ELGOHARY Kareem