The world is now approaching the era of medical digitalisation. All types of medical data from CT, MRI to EHR/EMR are programmed into a computer-readable format. Meanwhile, we also see new diagnostic technologies being approved by the FDA every year and more affordable genome sequencing tests available in the market. However, it is beyond the capability of a medical specialist to read and utilise all information for medical decision purposes.
The rapid advances in artificial intelligence and machine learning have demonstrated that deep learning technologies have superiority in solving various medical data analysis and prognosis tasks, thanks to the massive parallel processing power of modern GPU. We believe it is time to bring AI technology and medical digitalised data together to accelerate diagnoses, personalise treatment and medicine, and optimise healthcare pricing.
In this session, Associate Professor Zongyuan Ge will show some case studies about his recent achievement in medical AI research in skin cancer diagnosis (dermatology) and epilepsy anti-seizure medication selection.
Associate Professor Zongyuan Ge conducts interdisciplinary research at the boundary between artificial intelligence, computer-aided diagnosis, biomedical engineering, medical imaging and machine learning and is multi-award winning medical information science and technology entrepreneur.
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