Work

Data for 'Deriving spatial features from in situ proteomics imaging to enhance cancer survival analysis'

Year: 2023

Type: dataset

Abstract: Additional data for 'Deriving spatial features from in situ proteomics imaging to enhance cancer survival analysis'

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.7796392

Authors: Dayao, Monica T., Trevino, Alexandro, Kim, Honesty, Ruffalo, Matthew, D'Angio, H. Blaize, Preska, Ryan, Duvvuri, Umamaheswar, Mayer, Aaron T., Bar-Joseph, Ziv

Institutions: Carnegie Mellon University, University of Pittsburgh

Language: English

Topic: Radiomics and Machine Learning in Medical Imaging

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

Open Access status: green

OpenAlex ID: W4393665565

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