The AI That Predicts Cancer Treatment Better Than Any Current Method: Hospitals Say Not Yet

This July, a Harvard Medical School team published a model called COMPASS that analyzes cancer patients' genetic data and predicts whether immunotherapy will work for them. It outperforms the 22 best existing methods by an average of 8.5 percent. In bladder cancer data, patients it predicted as responders had an 86 percent one-year survival rate versus 40 percent for predicted non-responders. The paper's closing note: these results cannot be used to deny a patient treatment. Same month, a Taiwanese TV station used AI to generate a typhoon track map with location errors. Eight hundred thousand people saw it. One AI, more accurate. One AI, wrong. Two stories that seem unrelated, but they're asking the same question. Immunotherapy transformed oncology over the past decade, but only 10 to 40 percent of patients respond, depending on cancer type. The rest endure side effects without benefit. Existing biomarkers for predicting who will respond are inconsistent across cancer types. COMPASS is much more accurate, and it explains its reasoning: which immune signal pathways blocked a treatment that should have worked. But it only sees genetic data. Patient age, cancer stage, medical history, prior treatments: the context a physician actually needs to make a decision. The model cannot see any of this. Its accuracy has also only been validated against past research data, not in prospective clinical trials. The typhoon map situation isn't about whether AI can draw maps. It can. The problem is that pre-AI workflows included verification: data source checks, human review, fact-checking. AI-generated direct output skipped those steps. One Taiwanese journalist proposed an alternative: use AI to operate existing mapping tools, pull from official weather databases, run fact-checking processes, then output. The speed AI brings is still there, but the human confirmation step in the middle isn't gone. COMPASS is waiting for the same kind of process. Prospective clinical trials, where it's tested in real clinical environments, where doctors can see its outputs alongside full patient context and confirm the match. That path is how its accuracy becomes something a clinical system can trust. For many families, cancer treatment decisions are among the most difficult they'll face. AI entering this space with higher accuracy is genuinely good. But higher accuracy and ready to use directly are two different things. That gap is closing. It hasn't closed yet. The typhoon map: eight hundred thousand people already saw it. COMPASS's data: still waiting for the trial.