P11 : Instant Skin Cancer Diagnosis: AI Hybrid Neural Networks with Precise Evolution Tracking


Students Anthony Efthimiadis
School HDSB - Oakville Trafalgar High School - Oakville
Level Intermediate 9/10 - Grade 9
Group Group 8 - Engineering and Computing II
Abstract The purpose of this research is to develop an AI-based software system capable of instantly diagnosing all major skin cancers and precancers in non-invasive dermoscopy images. This project introduces innovative technologies like precise evolution tracking and AI-explainable reasoning to accelerate diagnosis and treatment processes, ultimately saving lives. Racial bias is addressed through a novel mathematical algorithm that normalizes skin tone/lighting variance.
Awards
Group Award Prize
ArcelorMittal Dofasco AwardsArcelorMittal Dofasco Information Systems Award$ 100
Hamilton Academy of Dentistry AwardsHamilton Academy of Dentistry Award - First$ 250
Merit AwardsGold Merit Award$ 100
Grand AwardsPrimary Fluid Systems Pinnacle Second Best in Fair$ 800
ISEF Trip AwardsISEF Trip Award
International Science & Engineering Affiliated Fair AwardsU.S. Agency for International Development (USAID) AwardCertificate & Social Network Media Kit
Farncombe Family Digestive Health Research AwardsFarncombe Family Digestive Health Research Institute Grand Award$ 750
Plus an interview
Ola Lunyk-Child Memorial Health AwardsOla Lunyk-Child Memorial Health Science Award - First$ 250