FDA reviewed artificial intelligence-enabled products applicable to emergency medicine

被引:0
|
作者
Morey, Jacob [1 ]
Schupbach, John [1 ]
Jones, Derick [1 ]
Walker, Laura [1 ]
Lindor, Rachel [1 ]
Loufek, Brenna [2 ]
Mullan, Aidan [1 ]
Cabrera, Daniel [1 ]
机构
[1] Mayo Clin, Dept Emergency Med, 200 1st St SW, Rochester, MN 55905 USA
[2] Mayo Clin, Ctr Digital Hlth, Rochester, MN USA
来源
关键词
Artificial intelligence; Machine learning; FDA; Emergency medicine; AI;
D O I
10.1016/j.ajem.2024.12.062
中图分类号
R4 [临床医学];
学科分类号
1002 ; 100602 ;
摘要
Objective: To identify and assess artificial intelligence (AI)-enabled products reviewed by the U.S. Food and Drug Administration (FDA) that are potentially applicable to emergency medicine (EM). Methods: The FDA AI-enabled products website was accessed to identify all marketed products as of March 2024. Board-certified EM physicians analyzed all products for applicability to EM practice. Inclusion criteria included products used by EM physicians directly or non-EM physicians participating directly in the evaluation and management of patients in an acute care setting. The Clinical and Economic Review (ICER) Evidence Rating Matrix was used to rate the net health benefit of applicable products. Results: A total of 882 AI-enabled products have been reviewed by the FDA from 1995 to 2024. There were 272 products that were updates of prior products that were excluded, leaving 610 unique products. Products were most commonly evaluated by Radiology (454/610), Cardiovascular (59/610), and Neurology (25/610) panels. We found 154 (25 %) products applicable to EM that were approved through Radiology (121/154), Cardiovascular (24/154), Neurology (5/154), Anesthesiology (3/154), and Ophthalmology (1/154) panels. There were 30 products that were rated as having a comparable or incremental net health benefit with moderate certainty (a C+ rating). Conclusion: An increasing number of AI-enabled products are available and regulated by the FDA. We have identified 154 that are applicable to EM, primarily related to assisting with diagnosis on various imaging modalities. There remain many opportunities for EM to assist in product reviews and meaningful translation of products into clinical practice. (c) 2024 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
引用
收藏
页码:241 / 246
页数:6
相关论文
共 50 条
  • [1] A Comprehensive Catalog of Emergency Medicine Applications of FDA-Regulated Artificial Intelligence-Enabled Products
    Morey, J.
    Schupbach, J.
    Lindor, R.
    Walker, L.
    Loufek, B.
    Jones, D.
    Cabrera, D.
    ANNALS OF EMERGENCY MEDICINE, 2024, 84 (04) : S33 - S33
  • [2] Artificial Intelligence-Enabled Science Poetry
    Kirmani, Ahmad R.
    ACS ENERGY LETTERS, 2022, 8 (01) : 574 - 576
  • [3] Artificial intelligence-enabled healthcare delivery
    Reddy, Sandeep
    Fox, John
    Purohit, Maulik P.
    JOURNAL OF THE ROYAL SOCIETY OF MEDICINE, 2019, 112 (01) : 22 - 28
  • [4] Artificial intelligence-enabled smart city construction
    Jiang, Yanxu
    Han, Linfei
    Gao, Yifang
    JOURNAL OF SUPERCOMPUTING, 2022, 78 (18): : 19501 - 19521
  • [5] Artificial intelligence-enabled enterprise information systems
    Zdravkovic, Milan
    Panetto, Herve
    ENTERPRISE INFORMATION SYSTEMS, 2022, 16 (05)
  • [6] Prediction of certainty in artificial intelligence-enabled electrocardiography
    Demolder, Anthony
    Nauwynck, Maxime
    De Pauw, Michel
    De Buyzere, Marc
    Duytschaever, Mattias
    Timmermans, Frank
    De Pooter, Jan
    JOURNAL OF ELECTROCARDIOLOGY, 2024, 83 : 71 - 79
  • [7] Artificial intelligence-enabled decision support in nephrology
    Tyler J. Loftus
    Benjamin Shickel
    Tezcan Ozrazgat-Baslanti
    Yuanfang Ren
    Benjamin S. Glicksberg
    Jie Cao
    Karandeep Singh
    Lili Chan
    Girish N. Nadkarni
    Azra Bihorac
    Nature Reviews Nephrology, 2022, 18 : 452 - 465
  • [8] Artificial intelligence-enabled smart city construction
    Yanxu Jiang
    Linfei Han
    Yifang Gao
    The Journal of Supercomputing, 2022, 78 : 19501 - 19521
  • [9] A BREAKTHROUGH IN ARTIFICIAL INTELLIGENCE-ENABLED MATERIALS DISCOVERY
    Bailey, Mary Page
    Chemical Engineering (United States), 2021, 128 (01):
  • [10] Clinical Evaluation of Artificial Intelligence-Enabled Interventions
    Hogg, H. D. Jeffry
    Martindale, Alexander P. L.
    Liu, Xiaoxuan
    Denniston, Alastair K.
    INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2024, 65 (10)