Certificate of Completion
THIS ACKNOWLEDGES THAT
HAS COMPLETED THE SPRING 2024 DEEP LEARNING BOOT CAMP
Henri Antikainen
Roman Holowinsky, PhD
MAY 03, 2024
DIRECTOR
DATE
TEAM
Medical Image Classification
Tristan Freiberg, Bailey Forster, Henri Antikainen
Melanoma can affect anyone and early detection is a crucial factor affecting survival rates. Machine learning models could assist trained healthcare professionals in screening for skin cancer. The Human Against Machine 10000 (HAM10000) dataset contains images of 7,470 distinct skin lesions, each belonging to one of seven mutually-exclusive classes of skin lesion, including melanoma, as well as other cancerous types and benign types such as nevi (moles). Our goal was to train a convolutional neural network (CNN) to accurately classify images of skin lesions using the HAM10000 dataset. The project includes a Streamlit app to test users’ classification ability against our fine-tuned models.