MACHINE LEARNING FOR HEALTH
RESEARCHERS
Our research aims at enhancing patient care by designing and enabling leading edge AI technologies in healthcare. Our expertise lies in developing, validating and clinically integrating socially responsible AI solutions to solve data analysis challenges encountered in different steps of the patient pathway: from prevention and triage, through diagnosis and decision making, to care delivery and management. Particularly, our research is focused on solving clinical challenges in medical image analysis, especially in the fields of radiology, cardiology, neonatology, and ophthalmology.
Topic areas: medical image analysis, healthcare, deep learning, radiology, ophthalmology
My research is focused on visual perception in the human brain using various brain imaging techniques, such as M/EEG, fMRI, TMS and ECoG, in combination with computational models, including both neurophysiologically-informed encoding models and deep neural networks developed in AI. The goal of my research is to find out how the human brain perceives and understands real-world scenes and videos.
Topic areas: computational neuroscience, deep learning, human perception, scene understanding, neuro imaging
Our research aims at enhancing patient care by designing and enabling leading edge AI technologies in healthcare. Our expertise lies in developing, validating and clinically integrating socially responsible AI solutions to solve data analysis challenges encountered in different steps of the patient pathway: from prevention and triage, through diagnosis and decision making, to care delivery and management. Particularly, our research is focused on solving clinical challenges in medical image analysis, especially in the fields of radiology, cardiology, neonatology, and ophthalmology.
Topic areas: medical image analysis, healthcare, deep learning, radiology, ophthalmology
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