广泛使用的人工智能医学测试关键临床研究的统计考虑和挑战:跨学科合作的机会

IF 1.5 4区 医学 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY Statistics in Biopharmaceutical Research Pub Date : 2023-01-18 DOI:10.1080/19466315.2023.2169752
Arkendra De
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引用次数: 1

摘要

摘要近年来,人工智能在医学检测中的应用受到了极大的关注,一系列已发表的研究证明了这一点,这些研究描述了为解决医学检测问题而开发的人工智能软件。虽然最近的这项活动令人兴奋,但只有在关键临床研究中表现出良好性能的情况下,开发的人工智能医学测试才能最终被视为广泛使用的候选测试。人工智能医学测试的关键临床研究是什么?在这种情况下,评估这些测试的性能的主要考虑因素和挑战是什么?统计学家与统计界以外的专业人士合作,可以在哪些方面提供帮助?本文解决了这些问题。这篇文章旨在吸引具有不同水平统计和医学检测知识的广大受众,以便加强学科间的合作。
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Statistical Considerations and Challenges for Pivotal Clinical Studies of Artificial Intelligence Medical Tests for Widespread Use: Opportunities for Inter-Disciplinary Collaboration
Abstract The application of Artificial Intelligence to medical testing has received much attention in recent years, as evidenced by the flurry of published studies describing Artificial Intelligence software developed to solve problems in medical testing. While this recent activity is exciting, developed Artificial Intelligence medical tests ultimately can only be considered as candidates for widespread use if these tests demonstrate good performance in pivotal clinical studies. What are pivotal clinical studies for Artificial Intelligence medical tests aimed for widespread use? What are some of the major considerations and challenges for assessing performance of these tests in this context? What are some of the outstanding areas where statisticians, in collaboration with professionals outside the statistical community, could help in this endeavor? This article addresses these questions. This article is meant to appeal to a broad audience with varying levels of statistical and medical testing knowledge so that inter-disciplinary collaboration could be enhanced.
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来源期刊
Statistics in Biopharmaceutical Research
Statistics in Biopharmaceutical Research MATHEMATICAL & COMPUTATIONAL BIOLOGY-STATISTICS & PROBABILITY
CiteScore
3.90
自引率
16.70%
发文量
56
期刊介绍: Statistics in Biopharmaceutical Research ( SBR), publishes articles that focus on the needs of researchers and applied statisticians in biopharmaceutical industries; academic biostatisticians from schools of medicine, veterinary medicine, public health, and pharmacy; statisticians and quantitative analysts working in regulatory agencies (e.g., U.S. Food and Drug Administration and its counterpart in other countries); statisticians with an interest in adopting methodology presented in this journal to their own fields; and nonstatisticians with an interest in applying statistical methods to biopharmaceutical problems. Statistics in Biopharmaceutical Research accepts papers that discuss appropriate statistical methodology and information regarding the use of statistics in all phases of research, development, and practice in the pharmaceutical, biopharmaceutical, device, and diagnostics industries. Articles should focus on the development of novel statistical methods, novel applications of current methods, or the innovative application of statistical principles that can be used by statistical practitioners in these disciplines. Areas of application may include statistical methods for drug discovery, including papers that address issues of multiplicity, sequential trials, adaptive designs, etc.; preclinical and clinical studies; genomics and proteomics; bioassay; biomarkers and surrogate markers; models and analyses of drug history, including pharmacoeconomics, product life cycle, detection of adverse events in clinical studies, and postmarketing risk assessment; regulatory guidelines, including issues of standardization of terminology (e.g., CDISC), tolerance and specification limits related to pharmaceutical practice, and novel methods of drug approval; and detection of adverse events in clinical and toxicological studies. Tutorial articles also are welcome. Articles should include demonstrable evidence of the usefulness of this methodology (presumably by means of an application). The Editorial Board of SBR intends to ensure that the journal continually provides important, useful, and timely information. To accomplish this, the board strives to attract outstanding articles by seeing that each submission receives a careful, thorough, and prompt review. Authors can choose to publish gold open access in this journal.
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