AI-powered diagnostics: What physicians need to know about artificial intelligence diagnosing patients

Artificial intelligence is rapidly transforming health care, and one of the most promising areas of innovation is diagnostics. From reading medical images to flagging abnormalities in lab results, AI tools are helping clinicians make faster, more accurate decisions. These systems use vast datasets and advanced machine learning algorithms to identify patterns that might be missed by the human eye—supporting earlier detection of conditions like cancer, heart disease, and diabetic retinopathy.

Hospitals and clinics are beginning to integrate AI into radiology, pathology, and even primary care settings, using tools that can prioritize urgent cases, reduce diagnostic errors, and streamline workflows. While these technologies aren’t replacing doctors, they’re enhancing clinical judgment and freeing up time for more direct patient care.

But this rapid expansion also raises important questions: How reliable are these tools across diverse populations? What role should AI play in decision-making? And how do we ensure transparency and accountability when machines are involved in diagnoses?

Medical Economics spoke with Mark Daly, chief technology officer of Digital Diagnostics, to learn more about how AI is changing how doctors diagnose patients, and the safeguards that need to be put in place to maintain both patient and physician trust.