Experienced Python / Machine Learning Developer Needed for Alzheimer’s Disease Detection

I am working on an academic research paper titled: "A Cross-Dataset Explainable Artificial Intelligence Framework for Early Alzheimer’s Disease Detection and Progression Prediction Using Multimodal MRI and Clinical Features." I am looking for an experienced individual freelancer (not an agency) who can implement the complete research methodology using Python and Google Colab. Project Requirements Download, preprocess, and organize ADNI and OASIS datasets, subject to approved data access. Perform structural MRI preprocessing and feature extraction. Integrate MRI-derived features with clinical features. Develop machine learning and deep learning models for Alzheimer’s disease classification. Implement cross-dataset validation (ADNI to OASIS and OASIS to ADNI, where compatible). Implement explainable AI techniques such as SHAP and Grad-CAM, where appropriate. Evaluate model performance using accuracy, precision, recall, F1-score, ROC-AUC and confusion matrices. Perform comparative analysis with baseline models. Provide complete Python source code and Google Colab notebooks. Prepare experimental results, graphs, tables and technical documentation suitable for an academic research paper. Required Skills Python Machine Learning Deep Learning Medical Image Processing MRI Analysis Alzheimer's Disease Prediction ADNI and OASIS datasets Explainable AI (XAI) SHAP TensorFlow / PyTorch Scikit-learn Freelancer Requirements Must have previous experience with medical imaging or healthcare AI projects. Experience working with ADNI or OASIS datasets is highly preferred. Must provide examples of previous relevant projects or publications. Must be an individual freelancer who personally performs the implementation. Must provide reproducible code and genuine experimental results. Expected Deliverables Complete implementation of the proposed framework. Preprocessing and feature extraction code. Trained models and evaluation results. Cross-dataset validation results. Explainability visualizations. Complete Google Colab notebooks and Python source code. Technical documentation. Important: I am looking for genuine research implementation and scientifically valid results. Please do not provide fabricated accuracy or experimental results.