Identification and extraction of family history information from clinical reports.
Many clinical reports contain family history, which is valuable information for clinical decision support and research. We developed a simple natural language processing algorithm to identify and extract family histories. The algorithm was tested on a set of discharge summaries and outpatient clinic notes. The precision and recall of extracting all diagnoses were 85.12% and 86.93%, respectively. The precision and recall of differentiating family history from patient history diagnoses were 96.30% and 92.86%, respectively. Both the precision and recall of exact family member assignment were 92.31%.
Goryachev
Sergey
S
Decision Systems Group, Brigham and Women's Hospital, Harvard Medical School,Boston, MA, USA.
Kim
Hyeoneui
H
Zeng-Treitler
Qing
Q
D001185:Artificial Intelligence; D005192:Family Health; D005568:Forms and Records Control; D016247:Information Storage and Retrieval / Q000379:methods*; D008487:Medical History Taking / Q000379:methods*; D016347:Medical Records Systems, Computerized; D009323:Natural Language Processing; D010363:Pattern Recognition, Automated; D014481:United States