Transforming Healthcare with Innovative AI Solutions
As a specialised Machine Learning Engineer based in Sydney, Luke (Guanhua) Cao delivers innovative AI solutions that transform healthcare workflows, enhance diagnostic accuracy, and improve patient outcomes.
What I Do
I develop AI-powered solutions for healthcare challenges. My expertise includes classical machine learning, clinical decision support systems, predictive patient monitoring, and healthcare data analytics. I focus on delivering accurate, interpretable models that help healthcare providers improve diagnosis, treatment planning, and patient care.
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Classical Machine Learning
95 % -
Clinical Decision Support
90 % -
Health Data Analytics
85 % -
Predictive Patient Monitoring
80 %
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Classical Machine Learning
Implementing statistical and ML algorithms including linear regression, gradient boosting trees, and random forests to analyse medical data, predict patient outcomes, and identify key factors for personalised treatment planning.
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Clinical Decision Support
Building AI systems that analyse patient data to provide evidence-based recommendations for diagnosis and treatment plans, helping clinicians make more informed decisions while reducing medical errors.
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Health Data Analytics
Analysing electronic health records and clinical notes using NLP to extract insights, identify trends, and generate structured data from unstructured medical text for improved patient care coordination.
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Predictive Patient Monitoring
Creating real-time monitoring systems that predict patient deterioration and adverse events before they occur, allowing for early intervention and improved outcomes in critical care settings.
Healthcare AI Projects
Explore innovative machine learning solutions that are transforming healthcare delivery and patient outcomes.
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Predictive Analytics
Health Roundtable Insights Platform
Developed advanced classical machine learning models powering the Health Roundtable Insights Platform's predictive forecasting capabilities. Implemented gradient boosting, random forests, and ensemble methods to enable interactive analytics for hospital performance metrics, clinical quality, patient safety, and operational efficiency.
See Project
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Clinical NLP
Clinical Notes Analysis
NLP system that extracts key medical information from clinical notes, converts unstructured text into structured data, and identifies potential medication interactions and adverse events.
See Project
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Predictive Patient Monitoring
Patient Deterioration Predictor
Real-time monitoring system that analyses vital signs and lab results to predict patient deterioration up to 24 hours before clinical signs appear, enabling early intervention in critical care units. This tool was found to improve patient outcomes as well as significantly reduce the length of stay by 5%.
See Project
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Clinical Coding
Auto Clinical Coding
Intelligent system that leverages LLM agents and Retrieval-Augmented Generation (RAG) to automatically generate accurate ICD and procedure codes from clinical health records, reducing manual coding effort by 70% while maintaining high compliance standards.
See Project
Ready to transform healthcare with AI?
Whether you're a hospital, research institution, or healthcare technology company, let's collaborate on creating innovative solutions for the future of medicine.