Massachusetts General Hospital, Lab of Medical Imaging and Computation
Intern (June 2022 – August 2022)
Developed high-accuracy PyTorch neural networks to classify X-ray images by body part, advancing lab research by visualizing model interpretability through heatmaps, ROC curves, and confusion matrices.
Developed neural networks with PyTorch to classify X-ray images based on corresponding body parts, achieving 99.3% accuracy rate
Contributed to research mission of lab by exploring techniques to present the importance of each image within model’s training dataset using visualizations such as heatmaps, ROC curves, and confusion matrices
Optimized and resolved hardware and software issues of high-performance servers used for research
