Gabriel Maicas is the AI Lead for the Women’s and Children’s Hospital (WCH) at The Australian Institute for Machine Learning (AIML). Gabriel leads the development and integration of state-of-the-art machine learning research into WCH to improve patient outcomes and experience, and hospital efficiency. Gabriel’s research focuses on a range of health fields where AI has the potential to benefit the broader society and have a greater impact on patients.
Previously, Gabriel was a research assistant at AIML focused on several health-AI areas including the early diagnosis of diseases and personalised medicine to improve treatment decisions. Gabriel obtained his PhD in Medical Image Analysis from The University of Adelaide (Australia) in 2018. Gabriel received his Master’s degree in Computer Vision from Universidad Rey Juan Carlos (Madrid, Spain) and graduated from Universidad Autonoma de Madrid (Madrid, Spain) with a double major in Mathematics and Computer Science.
Great research comes from sharing ideas. I acknowledge all collaborations, they inspire me and help me grow.
PhD in Medical Image Analysis, 2018
The University of Adelaide
MsC. Computer Vision, 2014
Universidad Rey Juan Carlos
Degree in Mathematics, 2013
Universidad Autonoma de Madrid
Degree in Computer Science, 2013
Universidad Autonoma de Madrid
Develop and Integrate AI at the Women’s and Children’s Hospital, Adelaide.
Early Disease Diagnosis
Personalised Medicine
Explainable AI
I was discussing about complex behaviours that emerge from AI at Café Sci: What Might Emerge?
Podcast in Spanish about polyp diagnosis with AI, Gastrointestinal Endoscopy, 2021
Interview about our polyp classification paper, The Lead, 2021
Intelligent machines to support, not replace, doctors, The University of Adelaide, 2019
AI helps makes breast scans more accurate, The Advertiser, 2018
Podcast Medical Imaging Training TechniquesData Skeptic, 2018
Media coverage about our work on Breast MRI Analysis: IT-Wire, Docteur Imago (Français), MedImaging (Español), etc.