Friday, May 10, 2024
Dr. Ali Loveys and Fiona Meng will present Laying the Foundation for AI-Ready Data on May 10, 2024, at 12 p.m.
Register now
About the Seminar
In September 2023, the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Central Repository announced the Data-Centric Challenge aimed at enhancing NIDDK data sets for future artificial intelligence (AI) applications. Challenge participants were tasked with generating an AI-ready data set that can be used for future data challenges and with producing methods to enhance the AI-readiness of NIDDK data. Teams utilized data from two longitudinal studies focused on type 1 diabetes (TEDDY and TrialNet).
The FI Consulting team, led by Dr. Ali Loveys, successfully consolidated and unified multiple TrialNet data sets and identified data outliers. The team enhanced raw data to ensure consistent variable representation and identified numeric and categorical “missingness” to prevent modeling bias, thus enhancing TrialNet data for AI-readiness. The team prepared a data set for time-series analysis, making the data more likely to inform prevention and personalized treatment plans for those at risk of diabetes and diabetes-related complications.
About the Speakers
Dr. Loveys is the Managing Director Healthcare at FI Consulting, a small-business government consultancy. She is dually board certified in primary care and clinical informatics. Dr. Loveys has more than 30 years of experience in leading emerging health information technology innovation, optimization, privacy, and security. Her work bridges clinical and business areas, IT policy, regulations, and standards to advance health care quality and safety.
Ms. Meng has a background in business analysis, data analysis, data science modeling, and machine-learning system design. As a data scientist at FI Consulting, she provides financial reporting automation solutions to clients and serves as a data scientist on internal projects. Ms. Meng is pursuing her Ph.D. in information systems at the University of Maryland, and her research focuses on the intersection of data science and machine learning in various applications.
