Project Code: SCI089
Project Description:
Acute pancreatitis is a complex condition with varying degrees of severity, and accurate prediction plays a crucial role in guiding timely interventions and improving patient outcomes.
Our project focuses on developing an automated machine learning system capable of predicting the severity of acute pancreatitis at an early stage. Early identification of severe cases can lead to timely interventions and improved patient management. Previous approaches use traditional neural networks, going beyond, we will investigate current state-of-the-art machine learning approaches.
Be a part of the Centre of Machine Learning for Social Good: Join our dynamic team. We are committed to advancing fundamental knowledge in machine learning and data analytics while tackling the most challenging health, environmental, and societal problems of our time. As the first center in Aotearoa dedicated to utilizing machine learning for social good, we collaborate closely with domain experts, leveraging their expertise as a catalyst to address high-impact societal issues.
Project Output:
The automated prediction system has the potential to enable healthcare professionals to intervene early, allocate resources effectively, and provide personalized treatment plans to acute pancreatitis patients.
Supervisors:
Gillian Dobbie,
Requirements:
1. Strong programming skills, particularly in Python, and familiarity with machine learning libraries (e.g., scikit-learn, TensorFlow)
2. Basic understanding of machine learning concepts and algorithms
3. Ability to work independently and collaboratively in a research team
4. Attention to detail and analytical mindset
5. Passion for improving healthcare outcomes through technology