Detection and Containment of Emerging Diseases Using AI Techniques

This proposal focuses on developing data-efficient and reliable algorithms for healthcare AI in response to emerging diseases such as CoVID-19. In particular, we aim to: 1) develop machine learning methods targeting unseen disease types; 2) adapt existing medical AI tools to emerging diseases to rapidly mitigate the outbreak; 3) develop robust methods to deploy and proliferate new disease models to disparate healthcare institutions across geographies; and 4) utilize collaborative AI approaches that leverage experiences of medical professionals to enable rapid cycle development of emerging disease models. We will deploy our experience in developing algorithms for incipient fault detection in cyber-physical systems and in generative modeling for synthetic data generation in computer vision applications and interactive machine learning. Proposed healthcare AI models will be made robust and explainable for clinical use in collaboration with the School of Medicine, University of California, San Francisco (UCSF). We will make extensive use of the C3.ai Data Lake, along with additional data available from UCSF. Further, we intend to use the C3.ai Suite extensively to facilitate our algorithmic and code development work. We will make our results openly available to foster further research. We also plan to integrate our results in the C3.ai Suite to make it more powerful in AI applications to healthcare.