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hash123shaikh/README.md

Hey there! 👋 I'm Hasan Shaikh

Clinical Data Scientist @ QIRAIL Lab, CMC Vellore

I work at the Quantitative Imaging Research and Artificial Intelligence Lab in the Department of Radiation Oncology at Ida B. Scudder Cancer Center, Christian Medical College, Vellore.

My day-to-day? Building AI models that help oncologists make better treatment decisions for head and neck cancer patients. I spend a lot of time working with CT and MRI scans, extracting features, and training deep learning models for automated segmentation.

What really drives me is seeing research translate into something tangible. Whether it's a predictive model that helps personalize radiotherapy or an auto-segmentation pipeline that saves clinicians hours of manual work.

I'm particularly interested in adaptive radiotherapy and how we can use AI to continuously optimize treatment plans based on how tumors respond.

🔍 Research Interests

Radiomics | Auto-segmentation | Large Language Models | Radiation Oncology Adaptive Radiotherapy | AI & Machine Learning | Deep Learning

🛠️ Tools I work with

Python PyRadiomics nnUNet MedSAM

Scikit-learn Pandas FastAPI Docker Git

📫 Connect with me

LinkedIn Portfolio Google Scholar

💡 "Advancing AI-driven oncology research through imaging and data science"

Pinned Loading

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    A perfect guide on how to prevent and remove `.env` files or sensitive data from GitHUb repositries. Includes cleanup commands, best practics, and sample files for safe code sharing.

  2. Master-Thesis Master-Thesis Public

    Multimodal deep learning for cancer survival prediction (91.2% accuracy, 79.8% sensitivity) using Gated Attention CNNs + Random Forest

    Python

  3. Reproducibility-of-HNC_CNN Reproducibility-of-HNC_CNN Public

    Python

  4. hnc-radiomics hnc-radiomics Public

    IBSI-compliant radiomics feature extraction pipeline for head and neck cancer CT imaging. Automated quantitative biomarker analysis from DICOM RT structure sets. Extracts 100+ shape, first-order, a…

    Jupyter Notebook