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.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.ajem.2024.12.062 | DOI Listing |
Am J Emerg Med
December 2024
Department of Emergency Medicine, Mayo Clinic, Rochester, MN, USA.
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).
View Article and Find Full Text PDFArtif Intell Med
December 2024
University College London, United Kingdom of Great Britain and Northern Ireland.
Front Digit Health
November 2024
Merck IT Centre, Merck Data & AI Organization, Merck Group, Bangalore, India.
Sensors (Basel)
November 2024
Interdisciplinary Institute, University of Aberdeen, Aberdeen AB24 3FX, UK.
The agri-food sector is undergoing a comprehensive transformation as it transitions towards net zero. To achieve this, fundamental changes and innovations are required, including changes in how food is produced and delivered to customers, new technologies, data and physical infrastructures, and algorithmic advancements. In this paper, we explore the opportunities and challenges of deploying AI-based data infrastructures for sustainability in the agri-food sector by focusing on two case studies: soft-fruit production and brewery operations.
View Article and Find Full Text PDFMicromachines (Basel)
October 2024
Institute for Macromolecular Chemistry, University of Freiburg, 79104 Freiburg, Germany.
Microfluidic devices (µFDs) have been explored extensively in drug screening and studying cellular processes such as migration and metastasis. However, the fabrication and implementation of microfluidic devices pose cost and logistical challenges that limit wider-spread adoption. Despite these challenges, light-based 3D printing offers a potential alternative to device fabrication.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!