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Using Natural Language Processing to Curate Unstructured Electronic Health Records into Research Ready Datasets
in partnership with the International COVID-19 Data Alliance, the Bill and Melinda Gates Foundation, and the Minderoo Foundation
What You Will Learn
This presentation provides an overview of Natural Language Processing (NLP), an Artificial Intelligence technique that can be used to curate unstructured medical records. We will see NLP in action as part of the ICODA Grand Challenges ‘PRIEST’ project (Pandemic Respiratory Infection Emergency System Triage) Study for Low and Middle-Income Countries as a case study.
Presenter
Eric Harvey has a passion for data and collaborating to turn that data into actionable information.A problem solver at heart, Eric focuses on identified cross-functional opportunities to increase efficiency and improve quality, including leveraging and adopting methodologies from other industries that positively impact early risk identification and selection of appropriate therapy targets. He leads MMS teams by keeping abreast of state-of-the-art technologies in data science and adaptive trial designs, and supporting initiatives that include risk management in data anonymization. Under his leadership in data science, MMS established a Health Analytics Collective with leading academic institutions.
Prior to MMS, Eric has led multiple biostatistics, programming, data science, data management, and information technology groups that include PRA Health Sciences, Health Decisions, and Quintiles (IQVIA). He holds several programming and quality certifications, including a six sigma black belt certification, and earned a Doctor of Philosophy in Biostatistics from the Virginia Commonwealth University School of Medicine. He also is actively involved in multiple industry organizations and routinely presents and teaches college courses on data science, statistics, and programming topics.