FDA-cleared artificial intelligence and machine learning-based medical devices and their 510(k) predicate networks

The Lancet Digital Health - Tập 5 - Trang e618-e626 - 2023
Urs J Muehlematter1,2, Christian Bluethgen1,3, Kerstin N Vokinger4
1Institute for Diagnostic and Interventional Radiology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
2Department of Nuclear Medicine, University Hospital Zurich and University of Zurich, Zurich, Switzerland
3Center for Artificial Intelligence in Medicine and Imaging, Stanford University, Stanford, CA, USA
4Faculty of Law, University of Zurich, Zurich, Switzerland

Tài liệu tham khảo

Hwang, 2019, Lifecycle regulation of artificial intelligence- and machine learning-based software devices in medicine, JAMA, 322, 2285, 10.1001/jama.2019.16842 Muehlematter, 2021, Approval of artificial intelligence and machine learning-based medical devices in the USA and Europe (2015-20): a comparative analysis, Lancet Digit Health, 3, e195, 10.1016/S2589-7500(20)30292-2 Redberg, 2019, Moving from substantial equivalence to substantial improvement for 510(k) devices, JAMA, 322, 927, 10.1001/jama.2019.10191 Johnston, 2020, Clinical evidence supporting US Food and Drug Administration clearance of novel therapeutic devices via the de novo pathway between 2011 and 2019, JAMA Intern Med, 180, 1701, 10.1001/jamainternmed.2020.3214 Dubin, 2021, Risk of recall among medical devices undergoing US Food and Drug Administration 510(k) clearance and premarket approval, 2008–2017, JAMA Netw Open, 4, 10.1001/jamanetworkopen.2021.7274 Ardaugh, 2013, The 510(k) ancestry of a metal-on-metal hip implant, N Engl J Med, 368, 97, 10.1056/NEJMp1211581 Rathi, 2019, Modernizing the FDA's 510(k) pathway, N Engl J Med, 381, 1891, 10.1056/NEJMp1908654 Kadakia, 2022, Renewing the call for reforms to medical device safety—the case of penumbra, JAMA Intern Med, 182, 59, 10.1001/jamainternmed.2021.6626 Zhu Hutson, 2017, AI glossary: artificial intelligence, in so many words, Science, 357, 19, 10.1126/science.357.6346.19 Yu, 2018, Artificial intelligence in healthcare, Nat Biomed Eng, 2, 719, 10.1038/s41551-018-0305-z Zhu, 2022, The 2021 landscape of FDA-approved artificial intelligence/machine learning-enabled medical devices: an analysis of the characteristics and intended use, Int J Med Inform, 165, 10.1016/j.ijmedinf.2022.104828 Luz, 2016, ECG-based heartbeat classification for arrhythmia detection: a survey, Comput Methods Programs Biomed, 127, 144, 10.1016/j.cmpb.2015.12.008 Hines, 2010, Left to their own devices: breakdowns in United States medical device premarket review, PLoS Med, 7, 10.1371/journal.pmed.1000280 Adashi, 2022, Deadly legacy—the 510(k) path to medical device clearance, JAMA Surg, 157, 185, 10.1001/jamasurg.2021.5558 Ross, 2015, High-risk medical devices: why do we not better understand effectiveness and safety?, JAMA Intern Med, 175, 939, 10.1001/jamainternmed.2015.0578 Horvath, 2023, Empirically assessing 510(k) device safety, SSRN Maisel, 2011 Kadakia, 2023, Use of recalled devices in new device authorizations under the US Food and Drug Administration's 510(k) pathway and risk of subsequent recalls, JAMA, 329, 136, 10.1001/jama.2022.23279