Evaluating and Reducing AI Model Group Disparity: An Analysis of COVID Test Outcomes in Children-Reference-Cited by-同舟云学术

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Evaluating and Reducing AI Model Group Disparity: An Analysis of COVID Test Outcomes in Children

Published:2023-12-13 Issue: Volume: Page:1511-1513
ISSN:
Container-title:2023 International Conference on Computational Science and Computational Intelligence (CSCI)
language:
Short-container-title:

Author:

Libin Alexander¹,Treitler Jonah T.²,Shao Yijun³

Affiliation:

1. Medstar Research Health Institute, Georgetown University,AIM AHEAD Consortium,Washington,D.C

2. Thomas Jefferson High School for Science and Technology,Alexandria,USA

3. George Washington University,Dept. of Clinical Research and Leadership,Washington,DC,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10590067/10590000/10590364.pdf?arnumber=10590364

Reference13 articles.

1. Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs

2. Deep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications

3. Protecting patient safety and privacy in the era of artificial intelligence

4. The Impact of Generative Conversational Artificial Intelligence on the Lesbian, Gay, Bisexual, Transgender, and Queer Community: Scoping Review

5. Bias in artificial intelligence in vascular surgery

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