Tag: Medical Imaging AI
Radiology AI, digital pathology, imaging foundation models, medical vision transformers, FDA SaMD clearance
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AI in Digital Pathology: What Computational Pathology Can and Cannot See
An NIH multi-institution study in Lancet Oncology classified 52 CNS tumor types from tissue images at 80% accuracy across 5,516 test samples. A Cancer Science paper simultaneously documented…
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FDA Clearance for AI Medical Devices: What 510(k), De Novo, and PMA Actually Mean
The FDA has cleared 700+ AI medical devices through 510(k), De Novo, and PMA pathways. A March 2026 European Radiology review documents how the EU AI Act, FDA…
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Radiology Foundation Models: What Merlin, the 22% Hallucination Rate, and ED Fracture Data Tell Us
Stanford published Merlin in Nature: a CT foundation model tested on 44,098 scans across 3 institutions. Meanwhile 22% of AI radiology reports contain factual errors and LLMs miss…
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AI in Radiology: Three Phases and What the Clinical Evidence Shows
Radiology AI has moved through three phases: rule-based CAD, the deep learning benchmark era, and clinical deployment validation. A 556-paper bibliometric analysis and a multicenter thymus CT validation…
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AI in Veterinary Medicine: What the Clinical Evidence Actually Shows
Veterinary AI is producing measurable results in canine radiology, equine PET imaging, gait analysis, and dairy herd monitoring. Six PubMed-indexed studies from 2024-2026 with specific accuracy numbers, and…
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