This project builds a multi-class disease classifier using symptom data. The trained model can predict the most likely disease given a set of symptoms and return a recommended treatment, dynamically ...
The 14.0 vs 168.0 gap between the evolved TA+sentiment policy and the noise-control policy (a factor of 12×) is the strongest single validation: the framework distinguishes signal from noise ...
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