- FUNDING
- May 2024
- Bulletin
Broadening Research Horizons
Faculty members receive grant by International Orthodontics Foundation, and Innovation and Technology Fund
Professor Dan Cho’s project aims to develop a smart dental aligner system to improve the orthodontic treatment.
Elite Research Grants -
International Orthodontics Foundation Research Grants
- Project title
- 3D-printed Smart Orthodontic Appliance Equipped with Nanodiamond Optical Sensor
- Principal investigator
- Professor Dan Cho, Assistant Professor in Dental Materials Science
- Co-investigators
- Professor Yanqi Yang, Clinical Professor in Orthodontics
- Professor Ji-Tae Kim, Associate Professor at HKU Department of Mechanical Engineering
This project aims to develop 3D-printed smart dental aligners integrated with optical nano-sensors, enabling real-time monitoring of orthodontic forces applied to the target teeth. The project will leverage scientific research and advanced additive manufacturing methods to create smart dental clear aligners with embedded flexible and transparent strain sensors.
The smart clear aligner system developed through this project is expected to significantly improve the quality and outcome of orthodontic treatment by easily and precisely measuring the magnitude and direction of the orthodontic forces. In addition to its application in orthodontic clear aligners, this technology has great potential for applications in implantable biosensors and advanced medical healing and monitoring.
“We hope that this project will serve as an opportunity to improve patients' overall oral health and open a new era in digital orthodontics,” said Professor Cho.
We hope that this project will serve as an opportunity to improve patients' overall oral health and open a new era in digital orthodontics
Professor Jade Teng’s project will harness the power of AI technology and sequence recognition to identify clinical fungi.
Public Sector Trial Scheme -
Innovation and Technology Fund
- Project title
- Trial: Diagnosing Fungal Infections by Artificial Intelligence (AI) - Development of a Refined Database Software Platform
- Principal Coordinator
- Professor Jade Teng, Associate Professor in Molecular Microbiology
The project aims to develop a software database platform that utilises AI technology and sequence recognition to electronically identify clinical fungi. Fungal infections pose a significant major global health risk, resulting in over 3.5 million deaths annually. However, timely diagnosis and treatment of these infections can be challenging. Currently, clinical microbiology laboratories rely heavily on morphological comparison to identify fungi recovered from patients, a process that is time-consuming, requires extensive expertise and demands significant manpower.
The AI-based fungal identification platform presents an efficient and cost-effective alternative to the conventional morphological comparison method. By harnessing the power of AI technology and sequence recognition, this platform enables early identification of fungal pathogens, facilitating prompt prescription of appropriate therapeutics.
“This innovative AI-based platform has the potential to revolutionise the diagnosis of fungal infections, making a significant impact in the healthcare industry,” said Professor Teng.