The mission of the AI in Medicine group is to develop and find effective computational techniques for the analysis of biomedical data. The group focuses on pursuing research, including:
We have a particularly strong interest in the application of computing technology to improve the diagnosis and stratification of patients and the management of patients with different diseases.
We aim to build a robust, state-of-the-art deep learning model for facial recognition that can help make patient care more efficient by allowing healthcare workers to access patients' data in a single, well-organized database. This deep learning-based approach also comes in as an innovative solution, in light of the current pandemic, enabling healthcare workers to offer ideal care with minimal patient contact, thus reducing their chances of contracting any communicable disease. We believe that facial recognition can have various applications in the healthcare domain, such as staff and visitor attendance, surveillance, etc.
Bachelor of Technology Electronics and Telecommunication Engineering, KIIT University, India
Danilo Tetesi, MSc.
Master in Cognitive Neuroscience, University La Sapienza, Italy
Ashwitha Devasya, MSc.
M. Sc. Advanced Computer Science with Big Data, University of Strathclyde, UK