By Mohamed Shabeebudeen KP | MBBS | M.Tech Medical Science & Technology, IIT Kharagpur
This portfolio showcases the intersection of clinical expertise and computational engineering. It includes projects ranging from foundational neural network architecture to deep learning for medical imaging.
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Custom Neural Network from Scratch Multi-layer backpropagation implemented in pure NumPy — no ML libraries used.
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Histopathology Image Classification Binary classification of malignant vs. benign tissue using CNNs (TensorFlow/Keras).
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10-Year Cardiovascular Risk Assessment Predicting CHD risk using Logistic Regression and clinical biomarkers.
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Breast Cancer Survival Analysis Outcome prediction using Decision Tree Classifiers on a 4,000+ patient cohort.
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Medical Insurance Cost Prediction Regression analysis of lifestyle risk factors on healthcare expenditure.
- Languages: Python
- Libraries: NumPy, Pandas, Scikit-learn, TensorFlow, Keras, Matplotlib, Seaborn
- Methods: Logistic Regression, Decision Trees, CNNs, Backpropagation, EDA