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Personalized Cancer Diagnosis is a tool that predicts the effect of genetic mutations in cancer patients. Given a gene, its variation, and clinical text, it uses advanced machine learning (Logistic Regression with TF-IDF features) to classify mutations into 9 categories.
This system is a machine learning-based web application built with Python, Scikit-learn, and Streamlit that predicts the probability of loan payback based on various features such as credit score, debt-to-income ratio, and employment status.