篇名

系統性規範人工智慧醫療器材軟體之必要性【全球瞭望】   免費試閱

並列篇名

The Need for a System View to Regulate Artificial Intelligence/Machine Learning-Based Software as Medical Device

中文摘要

如若把人工智慧(AI)與機器學習(ML)引入醫療領域中,將可望顯著改善醫療服務,例如:提供疾病的早期診斷,或是推薦最佳的個人化治療方案。然而,AI/ML在醫療領域的出現,也為政策制定者帶來許多挑戰。監管機構應該審查哪些使用AI/ML的產品?使用AI/ML的醫材軟體必須具備哪些證據才能批准上市?我們如何確保使用AI/ML的醫材軟體隨著時間及新數據的採用,其安全性及有效性是否有所改變?美國食品藥物管理局(FDA)最近提出一份討論文件來解決其中問題,然而FDA卻忽略了一個重點:我們認為,如同FDA這些主管機關需要擴大其監管其範圍,應從評估AI/ML醫療產品,擴大到評估整個系統。這種觀點的轉變—從產品觀點到系統觀點—對於在醫療領域中,極大程度地提高AI/ML的安全性與有效性是極其重要的,但是這種轉換為這些像FDA已經習慣監管產品而非系統的主管機關帶來了極大的挑戰。因而,我們將在下文提出一些建議,協助這些主管機關面對這些相當具挑戰性、但也十分重要的轉變。

英文摘要

However, the emergence of AI/ML in medicine also creates challenges, which regulators must pay attention to. Which medical AI/ML-based products should be reviewed by regulators? What evidence should be required to permit marketing for AI/ML-based software as a medical device (SaMD)? How can we ensure the safety and effectiveness of AI/ML-based SaMD that may change over time as they are applied to new data? The U.S. Food and Drug Administration (FDA), for example, has recently proposed a discussion paper to address some of these issues. But it misses an important point: we argue that regulators like the FDA need to widen their scope from evaluating medical AI/ML-based products to assessing systems. This shift in perspective — from a product view to a system view — is central to maximizing the safety and efficacy of AI/ML in health care, but it also poses significant challenges for agencies.

起訖頁

111-125

出版單位
DOI

10.53106/241553062022020064008  複製DOI  DOI查詢

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