کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4966774 1449297 2017 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Automatic prediction of coronary artery disease from clinical narratives
ترجمه فارسی عنوان
پیش بینی خودکار بیماری عروق کرونر از روایت های بالینی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی


- We propose a system to predict coronary artery disease from clinical narratives.
- We employ an ontology-guided approach to feature extraction.
- The system achieves state-of-the art performance of 77.4% F1-score.

Coronary Artery Disease (CAD) is not only the most common form of heart disease, but also the leading cause of death in both men and women (Coronary Artery Disease: MedlinePlus, 2015). We present a system that is able to automatically predict whether patients develop coronary artery disease based on their narrative medical histories, i.e., clinical free text. Although the free text in medical records has been used in several studies for identifying risk factors of coronary artery disease, to the best of our knowledge our work marks the first attempt at automatically predicting development of CAD. We tackle this task on a small corpus of diabetic patients. The size of this corpus makes it important to limit the number of features in order to avoid overfitting. We propose an ontology-guided approach to feature extraction, and compare it with two classic feature selection techniques. Our system achieves state-of-the-art performance of 77.4% F1 score.

99

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Biomedical Informatics - Volume 72, August 2017, Pages 23-32
نویسندگان
, , ,