Work

Deep learning on genome-wide association studies to predict the patient-specific risk of radiation-induced erectile dysfunction

Year: 2026

Type: article

Study design: Observational Study

Source: Radiotherapy and Oncology

DOI: 10.1016/j.radonc.2026.111531

Authors: Jung Hun Oh, Paul Auer, William Hall, Barry S. Rosenstein, Joseph O. Deasy, Sarah Kerns

Institutions: Memorial Sloan Kettering Cancer Center, Medical College of Wisconsin, Icahn School of Medicine at Mount Sinai

Language: English

Topic: Genetic Associations and Epidemiology

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: green

Funders: Breast Cancer Research Foundation, National Cancer Institute

Awards: G24641535, Multi-cohort validation of machine learning radiogenomic models (ML-RGx) to predict late toxicity in prostate cancer

OpenAlex ID: W7153475311

FWCI:

Cites: 44

Cited by:

Related to: 10