Characterizing the Clinical Adoption of Medical AI Devices through U.S. Insurance Claims-Reference-Cited by-同舟云学术

Characterizing the Clinical Adoption of Medical AI Devices through U.S. Insurance Claims

Published:2023-12-11 Issue:1 Volume:1 Page:
ISSN:2836-9386
Container-title:NEJM AI
language:en
Short-container-title:NEJM AI

Author:

Wu Kevin¹^ORCID,Wu Eric²^ORCID,Theodorou Brandon³^ORCID,Liang Weixin⁴^ORCID,Mack Christina⁵^ORCID,Glass Lucas⁵^ORCID,Sun Jimeng³⁶^ORCID,Zou James¹²⁴^ORCID

Affiliation:

1. Department of Biomedical Data Science, Stanford University, Stanford, CA

2. Department of Electrical Engineering, Stanford University, Stanford, CA

3. Department of Computer Science, University of Illinois Urbana-Champaign, Urbana, IL

4. Department of Computer Science, Stanford University, Stanford, CA

5. IQVIA, Durham, NC

6. Carle Illinois College of Medicine, University of Illinois Urbana-Champaign, Urbana, IL

Publisher

Massachusetts Medical Society

Reference88 articles.

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2. How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals

3. External Validation of a Widely Implemented Proprietary Sepsis Prediction Model in Hospitalized Patients

4. Wu E. Wu K. Zou J. Explaining medical AI performance disparities across sites with confounder Shapley value analysis. Cornell University. November 12 2021 (https://arxiv.org/abs/2111.08168).

5. Diagnostic Accuracy of Digital Screening Mammography With and Without Computer-Aided Detection

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