Khalid Latif

Title Challenges in Healthcare Risk Modeling- Case of Contrast-Induced Acute Kidney Injury
Abstract

The use of intravascular iodinated contrast agents is very common for patients undergoing Percutaneous Coronary Intervention. Risks associated with the intravascular administration of iodinated contrast agents are already recognized in literature and practice. It is, therefore, essential to reduce doses of intravenous iodinated contrast media. Identifying a safe contrast volume dose based on a patient's risk profile is nevertheless a challenging task. This talk will highlight the challenges and will present this as an open problem that is still in search of a reasonably accurate solution by exploring new predictors and deep learning algorithms.

Bio

Dr. Khalid Latif loves building teams and products that leverage data to solve complex problems and reveal meaningful insight using Machine Learning and Linked Data. He has helped various organizations in the design and development of intelligent information systems such as clinical process optimization and healthcare analytics, social media trend analysis and news prediction, risk management for customs, fault identification in the construction sites, and automated job application filtering and trend prediction. Khalid holds a Ph.D. degree in Data Science from Vienna University of Technology and has written over 50 publications. His work in this area also includes the contribution in multiple research projects supported by the Austrian Science Fund, National ICT R&D Fund, HEC, WIPO, and the World Bank.