AIMC Topic: United States Food and Drug Administration

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Regulatory Issues and Challenges to Artificial Intelligence Adoption.

Radiologic clinics of North America Nov 1, 2021
Artificial intelligence technology promises to redefine the practice of radiology. However, it exists in a nascent phase and remains largely untested in the clinical space. This nature is both a cause and consequence of the uncertain legal-regulatory...
Diagnostic Imaging Radiology United States Food and Drug Administration Image Interpretation, Computer-Assisted Humans Artificial Intelligence United States
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Machine Learning: The Next Paradigm Shift in Medical Education.

Academic medicine : journal of the Association of American Medical Colleges Jul 1, 2021
Machine learning (ML) algorithms are powerful prediction tools with immense potential in the clinical setting. There are a number of existing clinical tools that use ML, and many more are in development. Physicians are important stakeholders in the h...
Humans Clinical Trials as Topic Evidence-Based Medicine History, 20th Century Stakeholder Participation United States Food and Drug Administration Curriculum Education, Medical Aged Male United States Diagnostic Imaging Physician-Patient Relations Delivery of Health Care Liability, Legal COVID-19 Testing Physicians Clinical Decision-Making Diabetic Retinopathy Female Machine Learning Algorithms
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Conflicting information from the Food and Drug Administration: Missed opportunity to lead standards for safe and effective medical artificial intelligence solutions.

Journal of the American Medical Informatics Association : JAMIA Jun 12, 2021
The Food & Drug Administration (FDA) is considering the permanent exemption of premarket notification requirements for several Class I and II medical device products, including several artificial Intelligence (AI)-driven devices. The exemption is bas...
Humans United States United States Food and Drug Administration Device Approval Artificial Intelligence Software Reproducibility of Results
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How machine learning is embedded to support clinician decision making: an analysis of FDA-approved medical devices.

BMJ health & care informatics Apr 1, 2021
OBJECTIVE: To examine how and to what extent medical devices using machine learning (ML) support clinician decision making.
Machine Learning United States United States Food and Drug Administration Equipment and Supplies Decision Making, Computer-Assisted Humans
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How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals.

Nature medicine Apr 1, 2021
Equipment and Supplies Databases as Topic Device Approval Algorithms United States United States Food and Drug Administration Humans Artificial Intelligence
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Unexpected Inequality: Disparate-Impact From Artificial Intelligence in Healthcare Decisions.

Journal of law and health Jan 1, 2021
Systemic discrimination in healthcare plagues marginalized groups. Physicians incorrectly view people of color as having high pain tolerance, leading to undertreatment. Women with disabilities are often undiagnosed because their symptoms are dismisse...
Social Discrimination Humans Patient Protection and Affordable Care Act Artificial Intelligence Healthcare Disparities Public Nondiscrimination Policies Delivery of Health Care United States Food and Drug Administration Decision Support Systems, Clinical Health Care Sector United States
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Addressing health disparities in the Food and Drug Administration's artificial intelligence and machine learning regulatory framework.

Journal of the American Medical Informatics Association : JAMIA Dec 9, 2020
The exponential growth of health data from devices, health applications, and electronic health records coupled with the development of data analysis tools such as machine learning offer opportunities to leverage these data to mitigate health disparit...
Health Status Disparities Software Government Regulation Humans United States Artificial Intelligence United States Food and Drug Administration Machine Learning Minority Groups
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Machine-Learning Implementation in Clinical Anesthesia: Opportunities and Challenges.

Anesthesia and analgesia Jun 1, 2020
Europe Workflow Confidentiality Data Collection United States Food and Drug Administration Medical Informatics Humans Anesthesia Clinical Competence Decision Support Systems, Clinical United States Machine Learning Decision Making Electronic Health Records Point-of-Care Systems
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Regulatory oversight, causal inference, and safe and effective health care machine learning.

Biostatistics (Oxford, England) Apr 1, 2020
In recent years, the applications of Machine Learning (ML) in the health care delivery setting have grown to become both abundant and compelling. Regulators have taken notice of these developments and the U.S. Food and Drug Administration (FDA) has b...
Humans Machine Learning United States Food and Drug Administration Health Services Research Medical Informatics Applications Delivery of Health Care United States Causality
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Machine Learning Uncovers Food- and Excipient-Drug Interactions.

Cell reports Mar 17, 2020
Inactive ingredients and generally recognized as safe compounds are regarded by the US Food and Drug Administration (FDA) as benign for human consumption within specified dose ranges, but a growing body of research has revealed that many inactive ing...
Excipients Mice, Inbred BALB C Retinyl Esters Animals Diterpenes Pharmaceutical Preparations Humans Drug Interactions Swine Glucuronosyltransferase ATP Binding Cassette Transporter, Subfamily B, Member 1 Biological Assay United States Abietanes Machine Learning United States Food and Drug Administration Female Hep G2 Cells Food
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