Work

Harnessing Artificial Intelligence and Machine Learning in Biomedical Applications with the Appropriate Regulation of Data

Year: 2021

Type: article

Abstract: Medical devices and systems are increasingly relying on software using artificial intelligence (AI) and machine learning (ML) algorithms to increase efficiency, provide better diagnoses, and increase the quality of care for patients. AI- and ML-based devices and systems have an advantage over traditional medical device systems because they are designed to learn and improve using large databases of actual or simulated patient data. However, the use of these datasets could introduce harmful biases to certain populations, restrict economic development if policy were to change in the future, and negatively impact healthcare. We recommend amending the Food Drug and Cosmetic Act to explicitly direct the Secretary of Health and Human Services to regulate databases used by AI systems and require that the premarket review of medical databases includes assessments of potential bias and security.

Source: Journal of Science Policy & Governance

DOI: 10.38126/jspg180102

Authors: Nicole Bonan, Jaclyn Brennan, Anthony Hennig, Mark Alexander Kaltenborn

Institution: George Washington University

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: diamond

OpenAlex ID: W3136715448