This repository contains the medical data science course codes, presented in "maktabkhooneh".

AI-driven Clinical Support System for early PDAC detection. Identifying metabolic decoupling (HbA1c/BMI) using a hybrid approach (Deterministic Logic + LLMs) to save lives through timely intervention.

ML-based heart disease risk prediction with explainability (SHAP) and Streamlit demo

Healthcare machine learning project that predicts heart disease risk using patient clinical data, exploratory analysis, and multiple classification algorithms to support early diagnosis and data-driven medical decision-making.

Machine learning–based prediction of 10-year cardiovascular disease risk using Framingham Heart Study data

Alzheimer’s Disease Prediction is a classification-based machine learning project aimed at predicting the likelihood of Alzheimer’s disease in elderly individuals using clinical and demographic features.

Machine-learning pipeline for the development and internal validation of postoperative complication prediction models in adult male circumcision, using de-identified single-center clinical data from Milan, Italy, including preprocessing, modeling, evaluation, and explainability.

Portfolio of clinical data science projects focused on reproducible analytics, risk prediction, and clinically meaningful modeling across structured healthcare datasets.

Survival analysis of diabetic patient readmission using Cox Proportional Hazards and Random Survival Forests, focusing on time-to-event modeling, risk stratification, and clinical interpretability.

Pipeline supervisionado para predição de risco cardiovascular com dados clínicos estruturados, engenharia de atributos, validação de modelos, interpretabilidade, métricas preditivas, inferência automatizada e aplicação interativa.