390 citations
- National Cancer InstituteUS6 papers
- Information Management ServicesUS2 papers
- Johns Hopkins UniversityUS2 papers
- Alberta Machine Intelligence InstituteCA1 paper
- American Cancer SocietyUS1 paper
- American College of RadiologyUS1 paper
- Aminu Kano Teaching HospitalNG1 paper
- Asan Medical CenterKR1 paper
- Athinoula A. Martinos Center for Biomedical ImagingUS1 paper
- Baylor College of MedicineUS1 paper
- Brigham and Women's HospitalUS1 paper
- Cairo UniversityEG1 paper
9 papers
High-dimensional partial linear model with trend filtering
Sang Kyu Lee, Erikka Loftfield, Hyokyoung G. Hong +1
Understanding the links between diet, metabolic changes, and health outcomes is a key focus in nutritional science and broader biological research. Analyzing relationships, such as…
Wasm-iCARE: a portable and privacy-preserving web module to build, validate, and apply absolute risk models
Jeya Balaji Balasubramanian, Parichoy Pal Choudhury, Srijon Mukhopadhyay +4
Objective: Absolute risk models estimate an individual's future disease risk over a specified time interval. Applications utilizing server-side risk tooling, such as the R-based iC…
Varying-coefficients for regional quantile via KNN-based LASSO with applications to health outcome study
Seyoung Park, Eun Ryung Lee, Hyokyoung G. Hong
Health outcomes, such as body mass index and cholesterol levels, are known to be dependent on age and exhibit varying effects with their associated risk factors. In this paper, we…
Increasing efficiency and reducing bias when assessing HPV vaccination efficacy by using non-targeted HPV strains
Lola Etievant, Joshua N. Sampson, Mitchell H. Gail
Studies of vaccine efficacy often record both the incidence of vaccine-targeted virus strains (primary outcome) and the incidence of non-targeted strains (secondary outcome). Howev…
Confidence Intervals for Prevalence Estimates from Complex Surveys with Imperfect Assays
Damon Bayer, Michael Fay, Barry Graubard
We present several related methods for creating confidence intervals to assess disease prevalence in variety of survey sampling settings. These include simple random samples with i…
Federated Learning Enables Big Data for Rare Cancer Boundary Detection
Sarthak Pati, Ujjwal Baid, Brandon Edwards +276
Although machine learning (ML) has shown promise in numerous domains, there are concerns about generalizability to out-of-sample data. This is currently addressed by centrally shar…