Detecting Positive Medical History Mentions

Bing Bai, Pierre-François Laquerre, Richard G. Jackson, Robert Stewart

Abstract: In medical practice, knowing the medical history of a patient is crucial for diagnosis and treatment suggestion. However, such information is often recorded in unstructured notes from doctors, potentially mixed with the medical history of family members and mentions of disorders for other reasons (e.g. as potential side-effects). In this work we designed a scheme to automatically extract the medical history of patients from a large healthcare database. More specifically, we first extracted medical conditions mentioned using a rule-based system and a medical gazetteer, then we classified whether such mentions reflected the patient's history or not. We designed our method to be simple and with little human intervention. Our results are very encouraging, supporting the potential for efficient and effective deployment in clinical practice.