Advanced AI Medical Intelligence Platform
Budget / SalaryHourly project
TypeFreelance project
LocationRemote
Posted1 hour ago
Project Description:
Developed an end-to-end AI-powered medical intelligence platform for analyzing chest X-ray images and assisting with disease prediction. The system uses Deep Learning with DenseNet121 to classify X-ray images into five categories: Normal, Pneumonia, Atelectasis, Cardiomegaly, and Effusion. Integrated Grad-CAM Explainable AI (XAI) to generate visual heatmaps highlighting regions of the X-ray that contributed to the model's prediction. Built REST APIs using FastAPI for image upload, prediction, model information, and health monitoring. The platform also supports prediction history and is designed for integration with AI-assisted medical report generation using LLMs.
Key Features
1. Medical Image Analysis – Processes chest X-ray images using deep learning.
2. Disease Classification – DenseNet121-based classification for 5 medical categories.
3. Explainable AI – Grad-CAM generates heatmaps to visualize important image regions.
4. FastAPI REST API – Provides scalable endpoints for image prediction and model services.
5. Prediction Results – Returns predicted condition and confidence score.
6. AI-Assisted Reporting – Designed to generate structured medical reports using LLM integration.
7. Prediction History – Supports storing prediction information, model version, confidence, and report details.
8. Deployment Ready – Structured for Docker/containerized deployment.
9. Validation & Safety – Includes input validation and medical-use disclaimers.
Developed an end-to-end AI-powered medical intelligence platform for analyzing chest X-ray images and assisting with disease prediction. The system uses Deep Learning with DenseNet121 to classify X-ray images into five categories: Normal, Pneumonia, Atelectasis, Cardiomegaly, and Effusion. Integrated Grad-CAM Explainable AI (XAI) to generate visual heatmaps highlighting regions of the X-ray that contributed to the model's prediction. Built REST APIs using FastAPI for image upload, prediction, model information, and health monitoring. The platform also supports prediction history and is designed for integration with AI-assisted medical report generation using LLMs.
Key Features
1. Medical Image Analysis – Processes chest X-ray images using deep learning.
2. Disease Classification – DenseNet121-based classification for 5 medical categories.
3. Explainable AI – Grad-CAM generates heatmaps to visualize important image regions.
4. FastAPI REST API – Provides scalable endpoints for image prediction and model services.
5. Prediction Results – Returns predicted condition and confidence score.
6. AI-Assisted Reporting – Designed to generate structured medical reports using LLM integration.
7. Prediction History – Supports storing prediction information, model version, confidence, and report details.
8. Deployment Ready – Structured for Docker/containerized deployment.
9. Validation & Safety – Includes input validation and medical-use disclaimers.
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