التفاصيل البيبلوغرافية
| العنوان: |
A machine learning approach to triaging patients with chronic obstructive pulmonary disease. |
| المؤلفون: |
Swaminathan, Sumanth, Qirko, Klajdi, Smith, Ted, Corcoran, Ethan, Wysham, Nicholas G., Bazaz, Gaurav, Kappel, George, Gerber, Anthony N. |
| المصدر: |
PLoS ONE; 11/22/2017, Vol. 12 Issue 11, p1-21, 21p |
| مصطلحات موضوعية: |
OBSTRUCTIVE lung disease treatment, DECISION support systems -- Medical applications, DISEASE exacerbation, MEDICAL triage, ALGORITHMS, PREVENTION |
| مستخلص: |
COPD patients are burdened with a daily risk of acute exacerbation and loss of control, which could be mitigated by effective, on-demand decision support tools. In this study, we present a machine learning-based strategy for early detection of exacerbations and subsequent triage. Our application uses physician opinion in a statistically and clinically comprehensive set of patient cases to train a supervised prediction algorithm. The accuracy of the model is assessed against a panel of physicians each triaging identical cases in a representative patient validation set. Our results show that algorithm accuracy and safety indicators surpass all individual pulmonologists in both identifying exacerbations and predicting the consensus triage in a 101 case validation set. The algorithm is also the top performer in sensitivity, specificity, and ppv when predicting a patient’s need for emergency care. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
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