University Of Arizona

This research used natural language processing and machine learning to develop algorithms to recognize diagnostic criteria in free text for autism spectrum disorder, to increase earlier diagnosis and treatment.

This project developed patient-tailored relevant warnings about drug-drug interactions and found that it reduced irrelevant alerts.

This study defined a knowledge base for a clinical decision support (CDS) tool and identified technology requirements for CDS design to optimize adoption of necrotizing enterocolitis prevention practices to support clinician decision making with the overall goal to improve the use of evidence-based practices for prevention and early recognition of NEC among premature infants.