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early-detection

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This project uses YOLO for real-time leukemia detection in blood samples and CNNs for classifying brain hemorrhages in MRI scans. It aims to support faster, more accurate medical diagnostics through deep learning.

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  • Python

This project uses YOLO for real-time leukemia detection in blood samples and CNNs for classifying brain hemorrhages in MRI scans. It aims to support faster, more accurate medical diagnostics through deep learning.

  • Updated
  • Python

Built an end-to-end deep learning pipeline using ResNet-50 to classify retinal images into five stages of Diabetic Retinopathy. Applied transfer learning, image preprocessing, and AUC-based evaluation on the APTOS 2019 Kaggle dataset, achieving a 94% validation AUC—offering real-world potential in clinical diagnosis automation.

  • Updated
  • Python

Breast cancer histopathology image segmentation using U-Net. This repository implements U-Net for accurate segmentation of cancerous regions. It includes data augmentation, mixed precision training, checkpointing, and evaluation metrics like Dice score to improve model performance.

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  • Jupyter Notebook

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