WA Health Hackathon 2023

Challenge 4: Preventing Melanomas

Challenge Statement: A cancer diagnosis is a significant moment for a patient and their support network. It often leads into a long period of treatment and support. Prevention and early detection play a big role in positive outcomes. How could we better track and support cancer patients through this journey?   

Can we pre-emptively identify potential patients through target interviews and other ongoing, cancer detection programs? 

Supporting Mentors

Richard Trethick – Department of Health 

Potential Focus Questions 

This is a complex Challenge and you may find it useful to consider the following questions when building out your prototype: 

  • Can we use different data types to predict the prevalence of melanoma (coastal locations, UV irradiance, location to medical services etc.)?  
  • Can we help group cancer patients according to their cancer stage?  
  • Can we predict a cancer patient’s outcome according to their participating in interviews and programs? 

Critical Concepts 

Emergency Departments and Hospitals are incredibly complex organisations. You may want to talk to your Challenge Mentors about the following ideas as you developing you prototype: 

  • Melanoma progression and diagnostic approaches.  
  • Current thinking around melanoma causes and contributory factors.  
  • Melanoma treatment approaches.  
  • Melanoma prevention approaches. 

Supporting Data Sets 

The Department of Health has produced a synthesised version of the WA Cancer Registry (WACR) to help resolve this Challenge. Since 1982, the Western Australian Cancer Registry has collected population-based incidence and mortality cancer data for use in the planning of health care services and the support of cancer monitoring, evaluation and research at local, national and international levels. The Registry included data points on: 

  • Age 
  • Nationality 
  • Location of diagnosis 
  • Type of diagnosis 
  • Morphology 
  • Melanoma specific details 

Potential Solution Pathways 

You are free to resolve this Challenge by developing your prototype in whatever means you may like. Our mentors, partners and organising team have thought of the following techniques as being viable methods to resolve the Challenge: 

  • Statistical models to measure melanoma occurrence.  
  • Spatial analysis of melanoma occurrence and other descriptors.  
  • Machine learning models predicting cancer prevalence and risk.