Skin Cancer Classification

2025 · 2025 Competition

Schools: None
Category: Humanitarian

Project Overview

One Liner: Developing a machine learning model to classify pigmented skin lesions using the HAM10000 dataset, aiming to expedite skin cancer diagnosis.

Abstract

Our Skin Cancer Classification project aims to develop a machine-learning model with the HAM1000 dataset. This data set contains over 10,000 images of different pigmented skin lesions. We aim to use this model to diagnose pigmented skin lesions automatically. With various deep learning techniques, we strive to classify conditions like melanoma, basal cell carcinoma, and other pigmented lesions, which will lessen the time for diagnosis.

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Team Members

Ashifur Rahman
Ashifur Rahman
Lead
Rabib Ayan
Rabib Ayan
Mark O'Donnell
Mark O'Donnell
Ziqing(Emily) Ye
Ziqing(Emily) Ye
Jerry Li
Jerry Li
Mengyang Xu
Mengyang Xu

Advisors

Filippos Vokolos
Filippos Vokolos

Stakeholders

Gabriele Romano