Transfer learning as an AI-based solution to address limited datasets in space medicine-Reference-Cited by-同舟云学术

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

Published:2023-02 Issue: Volume:36 Page:36-38
ISSN:2214-5524
Container-title:Life Sciences in Space Research
language:en
Short-container-title:Life Sciences in Space Research

Author:

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

Funder

National Aeronautics and Space Administration

Publisher

Elsevier BV

Subject

Health, Toxicology and Mutagenesis,Astronomy and Astrophysics,Ecology,Radiation,Agricultural and Biological Sciences (miscellaneous)

Reference15 articles.

1. Medical image analysis using convolutional neural networks: a review;Anwar;J. Med. Syst.,2018

2. Transfer learning with convolutional neural networks for classification of abdominal ultrasound images;Cheng;J. Digit Imaging,2017

3. A transfer learning–based active learning framework for brain tumor classification;Hao;Front. Artif. Intell.,2021

4. Transfer learning for medical image classification: a literature review;Kim;BMC Med. Imaging,2022

5. Detection of anaemia from retinal fundus images via deep learning;Mitani;Nat. Biomed. Eng.,2020

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2. FA4SANS-GAN: A Novel Machine Learning Generative Adversarial Network to Further Understand Ophthalmic Changes in Spaceflight Associated Neuro-Ocular Syndrome (SANS);Ophthalmology Science;2024-07

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5. Application of Artificial Intelligence in Aerospace Engineering and Its Future Directions: A Systematic Quantitative Literature Review;Archives of Computational Methods in Engineering;2024-04-16

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