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We next sought to understand the drivers and barriers to the adoption of AI-guided image analysis (also referred to as computational pathology or CP). The top value proposition for AI-guided analysis is to enable biomarker detection that is difficult or impossible to score manually, such as PD-L1 (Figure 3).
Perspectives on Reducing Barriers to the Adoption of Digital and Computational Pathology Technology by Clinical Labs
The largest medical #AI randomized controlled trial yet performed, enrolling >100,000 women undergoing mammography screening, was published today @LancetDigitalH
The use of A.I. led to 29% higher detection of cancer, no increase of false positives, and reduced workload compared with radiologists without A.I.. https://t.co/GGrLqdG5yq
Eric Topolx.com
BIG new study: A new AI cancer detection model trained to spot pancreatic malignancies—the most deadly solid cancer— outperformed expert radiologists https://t.co/6UjQF5uXvU