Elad Walach[email protected]AI3 predictions for radiology AI in 2021With virtual RSNA 2020 over and the year drawing to a close, Elad Walach of artificial intelligence (AI) developer Aidoc has taken the time to share his predictions about trends in the world of radiology AI for next year.December 14, 2020AI5 reasons why imaging AI is different from CADArtificial intelligence (AI) in medical imaging is on the rise and already becoming part of the standard of care. But with all the hype, one must ask: Is next-generation imaging AI simply a new take on computer-aided detection/diagnosis (CAD)? Aidoc CEO Elad Walach presents five reasons why AI is fundamentally different.October 28, 2018AI3 ways to ensure AI algorithms are really workingArtificial intelligence (AI), deep learning, and related technologies have emerged as solutions that can really make a difference in almost every medical field imaginable, from radiology to pharmaceuticals to diagnosis. But the question remains: How do we know that these algorithms are actually working?August 5, 2018Page 1 of 1Top StoriesWomens ImagingWomen's Imaging MinnieCast, Episode 13: Partial breast irradiation in the spotlightTwo committee members for ASTRO's PBI guidelines share insights about this breast cancer treatment option.AIRadiology dominates thirty years of FDA AI device approvalsRadiologic TechnologistPetition seeks to increase number of attempts for taking ARRT examLegislationSocieties applaud introduction of Patients First ActEconomics2027 MPFS proposed rule would lift radiology reimbursement
![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)
