An Adaptive and Interpretable Framework for Biomedical Image Analysis-Reference-Cited by-同舟云学术

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An Adaptive and Interpretable Framework for Biomedical Image Analysis

Published:2023-10-29 Issue: Volume:34 Page:1156-1160
ISSN:
Container-title:2023 57th Asilomar Conference on Signals, Systems, and Computers
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Author:

Singh Samarth¹,Acton Scott T.²,Moosa Shayan³,Sheybani Natasha D.¹

Affiliation:

1. University of Virginia,Dept. of Biomedical Engineering,Charlottesville,VA,USA

2. University of Virginia,Dept. of Electrical and Computer Engineering,Charlottesville,VA,USA

3. University of Virginia Health System,Dept. of Neurosurgery,Charlottesville,VA,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10476702/10476779/10476986.pdf?arnumber=10476986

Reference21 articles.

1. Automated image analysis identifies signaling pathways regulating distinct signatures of cardiac myocyte hypertrophy

2. Artificial Intelligence in Colorectal Cancer Screening

3. Artificial intelligence in brain MRI analysis of Alzheimer’s disease over the past 12 years: A systematic review

4. Towards an effective and efficient deep learning model for COVID-19 patterns detection in X-ray images

5. Computer-aided prognosis: Predicting patient and disease outcome via quantitative fusion of multi-scale, multi-modal data

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