Artificial Intelligence in Radiography for Beginners

Date: 20th March 2020

Venue: Centre of Healthcare Innovation L6-006

Time: 6.00 pm - 9.20 pm

Speaker Bio

Dr. Poh Pei Ghim

Chief Medical Informatics Officer

   Dr Poh Pei Ghim received his Medical Degree from the University of Glasgow in 2012. He is also a software developer trained in Machine Learning and had developed AI modules that could recognise features on images such as X-rays. He was the first author of a published paper regarding MRI safety in cardiac pacemaker imaging and this was presented in conferences in Singapore and Toronto. This won the bronze award at the American Roentgen Ray Society Meeting 2015, one of the largest radiological scientific meetings in the world.

   In 2017, he joined iDOC Clinic as a co-founder to pursue his interest in medical informatics with the aim to deliver telemedicine and other high-tech medical solutions to the community. Between 2017-2019, Dr Poh created the iDOC Telemedicine Suite, Virtual Queue, Online Triage service as well as headed the Telebooth projects in both ITE and Unity Pharmacies and in 2018, Dr Poh completed the requirements to become a Certified HIPAA Professional.

   The EasyCare program was also developed by Dr Poh, that allowed patients and companies to access telehealth features provided by iDOC Clinic and tools allowing for remote diagnoses, risk assessments, health tracking and data analytics. Beyond his research and software development activities at iDOC Clinic and EasyCare, Dr Poh is also a director of Xellink since 2011 and continues his contribution to the open source community including tutorials, with special focus in Linux operating systems, machine learning and artificial intelligence. Most of these are available freely for reference for non-commercial use.

   Dr Poh Pei Ghim currently serves as the Chief Medical Informatics Officer at iDOC Clinic Medical Group and is a director of EasyCare Pte Ltd and Xellink Pte Ltd.

Workshop Objectives

• Introduce artificial intelligence (AI) and machine learning (ML).
• Application of AI and ML to solve gaps in Radiography. 

Directional Guide