About Us
The Data Science & AI Team provides the technical expertise and scientific computing infrastructure needed to extract, quality control, and manage diverse clinical and research data. Based on the curated data the team is creating multi-modal machine learning models for predictive analytics using the latest AI methods to discover new insights in basic research, clinical research, and translational medicine.
Data Science and Artificial Intelligence / Machine Learning (AI/ML) encompass diverse disciplines aimed at extracting valuable insights from structured and unstructured data through scientific methods, data mining, and big data analytics. Within basic and clinical research, and healthcare, copious amounts of multi-modal data are generated, including patient demographics, treatment records, medical test results (imaging, labs, pathology, genetics), and insurance data. Moreover, the proliferation of national and international health registries, public health and population data sources, personal wellness and health trackers, and Internet of Things (IoT) devices has further enriched the pool of data available for analysis by data scientists.
In healthcare practice and research, data science and AI/ML play a pivotal role in processing, managing, analyzing, and synthesizing this vast and varied amount of data produced by healthcare systems. Effective management and analysis of this data are essential for obtaining accurate and actionable insights. Techniques such as data cleansing, data validation, data integration, and data analysis are integral to extracting meaningful information from healthcare data for investigators. Such curated and validated data sets can then be used as training bases for creating AI/ML predictive and prescriptive analytical models.