AI-Powered Diagnostics in Primary Healthcare Opportunities, Limitations, and Ethical Considerations

Abstract

Primary healthcare is being transformed with artificial intelligence (AI), changing the healthcare landscape by increasing diagnosis accuracy, clinical operations efficiencies, and access to healthcare. This review provides an evidence synthesis of 25 peer-reviewed latest studies used to investigate the evidence of AI-powered diagnostics in primary care. Some opportunities are sophisticated disease detection, risk prediction, clinical decision support systems (CDSS), and improved access in underprivileged areas. The constraints include the quality of data, biases in algorithms, integration weak points, and gaps in the validation. Patient privacy, equity, accountability, and trust are some of the important ethical issues that pose hindrances. The review highlights that validation, standardized integration, and ethical models provide the most substantial protection of safety, equity, and efficacy of diagnostics performed through AI in the primary healthcare practice.