In this talk, we will discuss the different applications of machine learning in the medical field. In particular, how deep learning techniques have made the automation of complex medical tasks possible, ranging from medical image diagnosis to radiological report generation to radiotherapy treatment planning. Instead of detecting objects in natural images, could we implement R-CNNs to detect and classify abnormalities in medical images? Reinforcement learning is gaining popularity in the gaming field; would it be possible to apply the same idea to treatment planning systems to provide accurate treatment recommendations to doctors? Is GAN able to generate scans with isotropic voxels from low-resolution medical images? We will discuss how some of these techniques can impact the medical world in reducing the discrepancies in the quality of healthcare in rural and urban areas.
Presenter: Ms. Evelyn Chee, Research Engineer, BioMind
Bio: Evelyn Chee graduated with a First Class Honours in Applied Mathematics from the National University of Singapore. She started her early work in deep learning back in 2016 on reinforcement learning. In 2018, she joined BioMind, which specialises in developing solutions using deep learning for the medical field. As a research engineer and team lead of the Radiotherapy Research Team, Evelyn has been deeply involved in fine-tuning BioMind’s medical image segmentation and registration processes.
About BioMind: BioMind's mission is to improve efficiency and patient outcomes by empowering doctors and healthcare professionals with advanced technologies built upon deep learning techniques. The company built one of the world's first AI machines that can accurately diagnose brain tumors, vascular diseases, and stroke-related conditions.
Lunch will be served. Please register to ensure we have an accurate catering order.