NYU Langone highlighted a study that shows that an AI algorithm designed for analyzing MRI images can detect sex-related differences in brain structure.
The findings shed light on the need for diversity in neurological and psychiatric research, NYU Langone said, in a news release.
"Our findings provide a clearer picture of how a living, human brain is structured, which may in turn offer new insight into how many psychiatric and neurological disorders develop and why they can present differently in men and women," said study senior author Yvonne Lui, MD.
The study used an AI machine-learning algorithm to analyze thousands of MRI brain scans from 471 men and 560 women. The results revealed that the algorithm could accurately distinguish between biological male and female brains by spotting patterns in structure and complexity that were invisible to the human eye.
Ultimately, a detailed understanding of how biological sex impacts the brain could help improve diagnostic tools and treatments for neurological disorders, according to the researchers.
The study was published online May 14 in Scientific Reports.
![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
