GigHz Study Reveals Radiology Dominance in AI Device Authorizations

LOS ANGELES, Oct. 6, 2026 /CourierPR/ -- GigHz, a physician-founded software and research company, today announced findings from a peer-reviewed study led by its founder, Pouyan Golshani, MD. The study, published in Cureus, found that 76.5% of 1,430 artificial intelligence and machine learning-enabled medical device authorization records were reviewed by the FDA's Radiology panel. The finding raises a question for health systems investing in AI: what makes a clinical workflow ready for the technology?

The study, by Golshani and Mary S. Joseph, examined entries in the FDA's public AI-enabled device list with authorization dates from September 1995 through December 2025. Radiology accounted for 1,094 records. Together, the Radiology, Cardiovascular, and Neurology panels accounted for 90.6%.

The authors reported 331 authorizations in 2025. Across the full study period, Pathology accounted for nine records, Microbiology for six, and Obstetrics and Gynecology for four. These are FDA review-panel categories, which do not map directly to every specialty or setting in which a device may be used.

Growth has been rapid. Annual authorizations averaged 1.8 per year from 1995 through 2014 and 264 per year from 2023 through 2025. The field is also made up largely of developers with a single listed AI device: of 740 companies, 502 (67.8%) had a single authorized device, while 13 companies (1.8%) accounted for 247 devices (17.3%). No authorizations were recorded under a psychiatry or behavioral health review panel.

Golshani sees radiology's established digital infrastructure as one explanation for the concentration. The study describes authorization patterns; it does not test what caused them.

From available data to useful clinical decisions

For developers and health systems, he argues, that means defining a specific clinical task, making the necessary data accessible, and testing the tool in the workflow where it will be used. A documentation tool and a system recommending treatment require different evidence and safeguards.

What the study measures

The analysis measures authorization records, not clinical adoption, patient benefit, or physician replacement. The FDA states that its AI-enabled device list is not comprehensive. It also does not capture the full range of healthcare AI, including software functions outside device regulation. A small number of records under a review panel does not establish that the corresponding specialty lacks AI tools.

Golshani has also published a policy brief on how state oversight of clinical decision-support software relates to federal device review: gighz.com/policy/clinical-decision-support-sb-503

Study reference

Golshani P, Joseph MS. Three Decades of Food and Drug Administration Authorizations of Artificial Intelligence/Machine Learning-Enabled Medical Devices: Persistent Specialty Concentration and the Care-Delivery Gap (1995-2025). Cureus. 2026;18(7):e112583. Published July 13, 2026. doi.org/10.7759/cureus.112583

GigHz is a physician-founded software and research company developing tools for clinical decision support, radiology reporting, and practice intelligence. Golshani's commercial work includes clinical AI software. This descriptive study does not evaluate or validate GigHz products.