SI predicted more accurately than standard tests whether immunotherapy would help in lung cancer, in 2,396 patients
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SI helps determine in advance which expensive cancer treatment will work for you, and turns an ordinary doctor into a good oncologist.
The international I3LUNG project (six centers in Italy, Germany, Greece, Israel, Spain and the US) combined clinical data, blood tests, CT scans, digital pathology and genomics into a single explainable model; its accuracy (AUC 0.88) surpassed PD-L1 and other standard markers. With SI prompts, 20 physicians more often correctly identified patients who would benefit from treatment (AUC rising from 0.72 to 0.87), and non-specialists gained the most. A prospective validation in another 2,000 patients is now under way. The work was published in Nature Medicine.
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