Work

A shallow convolutional neural network predicts prognosis of lung cancer patients in multi-institutional computed tomography image datasets

Year: 2020

Type: article

Source: Nature Machine Intelligence

DOI: 10.1038/s42256-020-0173-6

Authors: Pritam Mukherjee, Mu Zhou, Edward Lee, Anne Schicht, Yoganand Balagurunathan, Sandy Napel, Robert Gillies, Simon Wong, Alexander Thieme, Ann Leung, Olivier Gevaert

Institutions: Stanford Medicine, Stanford University, Charité – Universitätsmedizin Berlin, Moffitt Cancer Center

Language: English

Topic: AI in cancer detection

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funders: U.S. Department of Health and Human Services, National Institutes of Health, National Cancer Institute, National Institute of Biomedical Imaging and Bioengineering

Awards: Radiogenomics Framework for Non-Invasive Personalized Medicine, G5619020794, Radiogenomics framework for non-invasive personalized medicine, Computing, Optimizing, and Evaluating Quantitative Cancer Imaging Biomarkers

OpenAlex ID: W3025872843

FWCI: 4.91

Cites: 72

Cited by: 101

Related to: 10