AI in Medicine
Research gap analysis derived from 2 medicine papers in our local library.
The gap
Future research should focus on improving data quality and minimizing error risks due to AI system imperfections while addressing ethical and regulatory considerations across various medical fields.
Consensus across the literature
The papers collectively establish the need for better data quality, ethical concerns, and regulatory frameworks but leave specific methodological improvements open.
Research trend
Emerging — attention growing, methods still coalescing.
Supporting evidence — 3 representative gaps
- INTELLIGENT DIAGNOSTICS IN ENDOCRINOLOGY: THE POTENTIAL OF ARTIFICIAL INTELLIGENCE IN THE DETECTION AND EVALUATION OF THYROID NODULES (2026) · doi
Future research should focus on improving data quality and minimizing error risks due to AI system imperfections, while also addressing ethical and regulatory considerations.
Keywords: future focus improving quality minimizing error risks system imperfections addressing ethical regulatory considerations - Artificial Intelligence in Radiology: Unlocking New Dimensions of Value (2026) · doi
Realizing the potential of AI requires overcoming significant hurdles that include ensuring data quality, improving model interpretability, addressing ethical and regulatory concerns, and bringing added value, as well as meeting the challenge of new reimbursement strategies.
Keywords: realizing potential requires overcoming significant hurdles include ensuring quality improving model interpretability addressing ethical regulatory - INTELLIGENT DIAGNOSTICS IN ENDOCRINOLOGY: THE POTENTIAL OF ARTIFICIAL INTELLIGENCE IN THE DETECTION AND EVALUATION OF THYROID NODULES (2026) · doi
Future research should focus on improving data quality and minimizing error risks due to AI system imperfections, while also addressing ethical and regulatory considerations. A significant limitation is the dependence of diagnostic effectiveness on input data quality.
Keywords: quality future focus improving minimizing error risks system imperfections addressing ethical regulatory considerations significant limitation
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