Work

Transfer learning as an AI-based solution to address limited datasets in space medicine

Year: 2023

Type: article

Source: Life Sciences in Space Research

DOI: 10.1016/j.lssr.2022.12.002

Authors: Ethan Waisberg, Joshua Ong, Sharif Amit Kamran, Phani Paladugu, Nasif Zaman, Andrew G. Lee, Alireza Tavakkoli

Institutions: University College Dublin, University of Michigan, Michigan Medicine, University of Nevada, Reno, Brigham and Women's Hospital, Harvard University, Thomas Jefferson University, University of Iowa, Houston Methodist, The University of Texas MD Anderson Cancer Center, Baylor College of Medicine, University of Iowa Hospitals and Clinics, Weill Cornell Medicine, Weill Cornell Medical Center, The University of Texas Medical Branch at Galveston, Texas A&M University

Language: English

Topic: Domain Adaptation and Few-Shot Learning

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: bronze

Funder: National Aeronautics and Space Administration

Award: G3795089887

OpenAlex ID: W4313380704

FWCI: 2.268

Cites: 14

Cited by: 26

Related to: 10