Work

SP-0484: Machine Learning of radiogenomics SNP GWAS to predict complication risk and to identify key biological correlates

Year: 2018

Type: conference-abstract

Source: Radiotherapy and Oncology

DOI: 10.1016/s0167-8140(18)30794-1

Authors: J. Deasy, S.K. Lee, J.H. Oh, S. Kerns, H. Orstrer, B. Rosenstein

Institutions: Memorial Sloan Kettering Cancer Center, University of Rochester Medicine, Albert Einstein College of Medicine, Icahn School of Medicine at Mount Sinai

Language: English

Topic: Radiomics and Machine Learning in Medical Imaging

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $3,770

OpenAlex ID: W2809304316

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