Current Work

Current Research Projects

Deep Learning for Medical Image Analysis

I’m currently working on developing advanced deep learning models for medical image segmentation and classification. This project focuses on improving the accuracy of disease detection in X-ray and MRI images using novel neural network architectures.

Key Achievements:

• Developed a new convolutional neural network architecture that improved accuracy by 15%
• Successfully implemented attention mechanisms for better feature extraction
• Currently working on making the model more interpretable for clinical use

Natural Language Processing in Healthcare

Another significant project involves analyzing clinical notes using state-of-the-art NLP techniques. We’re working on:

• Automated extraction of medical conditions from physician notes
• Prediction of patient outcomes based on historical data
• Development of more efficient clinical documentation systems

Recent Updates

October 2024: Presented our initial findings at the International Conference on Machine Learning in Healthcare September 2024: Published a paper on our novel segmentation algorithm August 2024: Started collaboration with Local General Hospital for data collection and validation

Follow along for regular updates on my research progress and new developments in these areas.