192 citations
- University of PennsylvaniaUS6 papers
- National Institutes of HealthUS3 papers
- University of SaskatchewanCA3 papers
- California University of PennsylvaniaUS2 papers
- Columbia UniversityUS2 papers
- Temple UniversityUS2 papers
- CEA Paris-SaclayFR1 paper
- Centre Lasers Intenses et ApplicationsFR1 paper
- Centre National de la Recherche ScientifiqueFR1 paper
- Children's Hospital of PhiladelphiaUS1 paper
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR1 paper
- Drexel UniversityUS1 paper
18 papers
Enhancing Phenotype Recognition in Clinical Notes Using Large Language Models: PhenoBCBERT and PhenoGPT
Jingye Yang, Cong Liu, Wendy Deng +4
We hypothesize that large language models (LLMs) based on the transformer architecture can enable automated detection of clinical phenotype terms, including terms not documented in…
LCS-DIVE: An Automated Rule-based Machine Learning Visualization Pipeline for Characterizing Complex Associations in Classification
Robert Zhang, Rachael Stolzenberg-Solomon, Shannon M. Lynch +1
Machine learning (ML) research has yielded powerful tools for training accurate prediction models despite complex multivariate associations (e.g. interactions and heterogeneity). I…
A Rigorous Machine Learning Analysis Pipeline for Biomedical Binary Classification: Application in Pancreatic Cancer Nested Case-control Studies with Implications for Bias Assessments
Ryan J. Urbanowicz, Pranshu Suri, Yuhan Cui +4
Machine learning (ML) offers a collection of powerful approaches for detecting and modeling associations, often applied to data having a large number of features and/or complex ass…
Probability Link Models with Symmetric Information Divergence
Majid Asadi, Karthik Devarajan, Nader Ebrahimi +2
This paper introduces link functions for transforming one probability distribution to another such that the Kullback-Leibler and Rényi divergences between the two distributions are…
A Numerical Transform of Random Forest Regressors corrects Systematically-Biased Predictions
Shipra Malhotra, John Karanicolas
Over the past decade, random forest models have become widely used as a robust method for high-dimensional data regression tasks. In part, the popularity of these models arises fro…
A Competing Risks Model with Binary Time Varying Covariates for Estimation of Breast Cancer Risks in BRCA1 Families
Yun-Hee Choi, Hae Jung, Saundra Buys +6
Mammographic screening and prophylactic surgery such as risk-reducing salpingo oophorectomy (RRSO) can potentially reduce breast cancer risks among mutation carriers of BRCA famili…