Abstract: AI has contributed a lot in healthcare. Infectious disease outbreak is no exception. The talk will provide a walk through about how AI-guided tools help in predicting/detecting infectious diseases, such as Pneumonia, TB, and Covid-19. Infectious disease prediction and unexploited data will be discussed, as predictive analytical tools are limited to education and training (at least for Covid19). It also covers shallow learning (handcrafted features) as well as deep learning mechanism in both image modalities: CT scan and Chest X-ray. Additionally, an obvious question, how big data is big will be discussed by taking two key points into account: data augmentation and transfer learning. Of course, the talk primarily focuses on the need of active learning in #AI4Healthcare, with a focus on Covid-19.

Biography: Professor KC Santosh, Ph.D., is Chair of the Department of Computer Science at the University of South Dakota (USD). He also serves International Medical University as an Adjunct Professor (Full). Before joining USD, he worked as Research Fellow at the US National Library of Medicine (NLM), National Institutes of Health (NIH). He was Postdoctoral Research Scientist at the Loria Research Centre (with industrial partner, ITESOFT (France)). He has demonstrated expertise in artificial intelligence, machine learning, pattern recognition, computer vision, image processing, and data mining with applications- such as medical imaging informatics, document imaging, biometrics, forensics and speech analysis. His research projects are funded (of more than $2m) by multiple agencies, such as SDCRGP, Department of Education, National Science Foundation, and Asian Office of Aerospace Research and Development. He is the proud recipient of the Cutler Award for Teaching and Research Excellence (USD, 2021), the President's Research Excellence Award (USD, 2019), and the Ignite from the U.S. Department of Health & Human Services (2014).