Roger LindahlRisk ManagementMore NIH research funds could aid imaging effortThe effort to establish a separate imaging institute at the National Institutes of Health (NIH) could get a boost after President Bill Clinton announced that he will be asking Congress for a substantial increase in fiscal 2001 funding for research at theJanuary 24, 2000Residents/FellowsRadiology accelerates drive for imaging institute in 2000The New Year is shaping up as make-or-break time in radiology's five-year effort to create a separate institute for imaging research at the National Institutes of Health (NIH).January 10, 2000Page 1 of 1Top StoriesEconomics2027 MPFS proposed rule would lift radiology reimbursementIf finalized, the proposed rule is expected to hike reimbursement by 2% for radiology, 2% for nuclear medicine, 3% for interventional radiology, and 3% for radiation oncology.MRIMRI could replace DRE for prostate cancer stagingMRIPetition asks FDA to implement new OEM rule for MRI safetyWomens ImagingIncorrect AI suggestions influence reader performance on mammographyMRIPodcast: MRI tragedy, key aspects of the Colombini family's lawsuit
![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&fit=crop&h=167&q=70&w=250)
![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)
