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个人简介
My main research focus is to develop machine learning methods that can help to decipher human disease heterogeneity. This involves combining data from multiple heterogeneous sources while addressing missing data and noise, simultaneous subtyping and feature selection in very sparse settings and more. Our contributions to machine learning include novel graph-based unsupervised feature selection methods and graphical models for subtyping in GWAS. We collaborate with clinicians to ensure that our work is relevant in the clinic.
研究兴趣
论文共 216 篇作者统计合作学者相似作者
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CoRR (2024)
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CoRR (2024)
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Bhavya Kasera,Shiri Shinar, Parinita Edke,Vagisha Pruthi,Anna Goldenberg,Lauren Erdman,Tim Van Mieghem
Prenatal diagnosis (2024)
Ping He,Theo J. Moraes,Darlene Dai, Myrtha E. Reyna-Vargas,Ruixue Dai,Piush Mandhane,Elinor Simons,Meghan B. Azad, Courtney Hoskinson,Charisse Petersen,Kate L. Del Bel,Stuart E. Turvey,
Pediatric Researchpp.1-8, (2024)
CoRR (2024)
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Cancer research communicationsno. 5 (2023): 738-754
medRxiv (Cold Spring Harbor Laboratory) (2023)
Lauren Erdman,Mandy Rickard, Kyla Velear,Daniel Alvarez,Kunj Sheth, Armando Lorenzo,Bo Wang,Anna Goldenberg
2023 19TH INTERNATIONAL SYMPOSIUM ON MEDICAL INFORMATION PROCESSING AND ANALYSIS, SIPAIMpp.1-6, (2023)
Machine Learning for Health Workshoppp.636-649, (2023)
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