The Case for Algorithmic Stewardship for Artificial Intelligence and Machine Learning Technologies-Reference-Cited by-同舟云学术

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The Case for Algorithmic Stewardship for Artificial Intelligence and Machine Learning Technologies

Published:2020-10-13 Issue:14 Volume:324 Page:1397
ISSN:0098-7484
Container-title:JAMA
language:en
Short-container-title:JAMA

Author:

Eaneff Stephanie¹²,Obermeyer Ziad³,Butte Atul J.²⁴

Affiliation:

1. Berkeley Institute for Data Science, University of California, Berkeley

2. Bakar Computational Health Sciences Institute, University of California, San Francisco

3. University of California, Berkeley School of Public Health

4. Center for Data-Driven Insights and Innovation, University of California Health, Oakland

Publisher

American Medical Association (AMA)

Subject

General Medicine

Link

https://jamanetwork.com/journals/jama/articlepdf/2770772/jama_eaneff_2020_vp_200118_1602283818.58345.pdf

Reference10 articles.

1. A framework for rationing ventilators and critical care beds during the COVID-19 pandemic.;White;JAMA,2020

2. Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs.;Gulshan;JAMA,2016

3. Dissecting racial bias in an algorithm used to manage the health of populations.;Obermeyer;Science,2019

4. A fairer way forward for AI in health care.;Nordling;Nature,2019

5. Deep learning predicts hip fracture using confounding patient and healthcare variables.;Badgeley;NPJ Digit Med,2019

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2. Medical Ethics of Large Language Models in Medicine;NEJM AI;2024-06-27

3. Artificial Intelligence Integration in Healthcare: Perspectives and Trends in a Survey of U.S. Health System Leaders;2024-06-13

4. Ethical and regulatory challenges of large language models in medicine;LANCET DIGIT HEALTH;2024

5. Ethical and regulatory challenges of large language models in medicine;The Lancet Digital Health;2024-06

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