The AI trust gap: what foundation models still lack in histopathology diagnosis
A discussion with Professor Tizhoosh on the gap between foundation models and the demands of clinical diagnosis: accuracy, consistency, speed,…
Waiv receives dual CE marking under IVDR: AI tests for breast and colorectal cancer enter clinical practice
Waiv has received CE marking under IVDR for two tests: RlapsRisk BC for breast cancer recurrence prediction and MSIntuit CRC for MSI screening…
Language models outperform doctors at summarizing cancer pathology reports: Northwestern Medicine study
A Northwestern Medicine study shows that open-source language models outperformed physicians at summarizing cancer pathology reports,…
Digital transformation in community laboratories: a lesson from South Bend
How a century-old nonprofit medical laboratory in Indiana moved into digital pathology, and what its experience shows about adoption barriers…
Liron Pantanowitz: from pathology informatics to AI in digital pathology
An interview with Professor Liron Pantanowitz on digital transformation in pathology at UPMC, the use of artificial intelligence, and the…
PathAI and MedStar Health partnership: deploying AISight® Dx digital pathology and AI algorithms across a large laboratory network
A multi-year strategic collaboration between PathAI and MedStar Health will deploy the AISight Dx platform and AI algorithms across a network…
Capsule sponge test with biomarkers: a new Barrett esophagus risk-stratification tool identifies an ultra-high-risk group with an 85% likelihood of dysplasia or cancer
A UK study of 910 patients shows that a capsule sponge test combined with biomarker analysis can identify more than half of patients with…
Multimodal models in digital pathology: how PathAI combines vision and language
From images alone to deeper interpretation. Most AI systems in pathology rely only on image analysis.…
Turning narrative pathology reports into structured data with AI
Pathology reports are written as free narrative text. Each pathologist has their own reporting style, and report formats vary between hospitals…
Brain CT predicts cardiovascular disease: Stanford JACC study finds hidden risk signals in routine emergency imaging
Stanford study in JACC: AI extracts cardiovascular risk information from routine head CT, outperforming the clinical PREVENT score (C-index…