Work

Investigating Useful Features for Overall Survival Prediction in Patients with Low-Grade Glioma Using Histology Slides

Year: 2022

Type: conference-paper

Source: Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

DOI: 10.1109/embc48229.2022.9871027

Authors: Elisa Warner, Xuelu Li, Ganesh Rao, Jason Huse, Jeffrey Traylor, Visweswaran Ravikumar, Vishal Monga, Arvind Rao

Institutions: University of Michigan, Pennsylvania State University, Amazon (United States), Baylor College of Medicine, The University of Texas MD Anderson Cancer Center, The University of Texas Southwestern Medical Center

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: closed

Funders: American Cancer Society, National Institutes of Health, National Cancer Institute, National Institute of General Medical Sciences

Awards: G1083577844, The University of Michigan Bioinformatics Training Program, Synthesizing Image-derived Heterogeneity with Genomic measurements for Assessing Disease Aggressiveness in Lower Grade Gliomas

OpenAlex ID: W4295511574

FWCI:

Cites: 9

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Related to: 10