Comparison of artificial neural network and logistic regression models for prediction of outcomes in trauma patients: A systematic review and meta-analysis

Comparison of artificial neural network and logistic regression models for prediction of outcomes in trauma patients: A systematic review and meta-analysis


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دانشگاه علوم پزشکی تبریز
دانشگاه علوم پزشکی تبریز

نویسندگان: مرتضی عرب زوزنی

کلمات کلیدی: Artificial neural network Logistic regression Trauma Systematic review

نشریه: 14889 , 2 , 50 , 2019

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نویسنده ثبت کننده مقاله مرتضی عرب زوزنی
مرحله جاری مقاله تایید نهایی
دانشکده/مرکز مربوطه دانشکده مدیریت و اطلاع رسانی پزشکی
کد مقاله 66093
عنوان فارسی مقاله Comparison of artificial neural network and logistic regression models for prediction of outcomes in trauma patients: A systematic review and meta-analysis
عنوان لاتین مقاله Comparison of artificial neural network and logistic regression models for prediction of outcomes in trauma patients: A systematic review and meta-analysis
ناشر 8
آیا مقاله از طرح تحقیقاتی و یا منتورشیپ استخراج شده است؟ خیر
عنوان نشریه (خارج از لیست فوق)
نوع مقاله Review Article
نحوه ایندکس شدن مقاله ایندکس شده سطح یک – ISI - Web of Science
آدرس لینک مقاله/ همایش در شبکه اینترنت

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known as models that extensively used in medical sciences. The aim of this study was to compare the ANN and LR models in prediction of Health-related outcomes in traumatic patients using a systematic review. Methods: The study was planned and conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) checklist. A literature search of published studies was conducted using PubMed, Embase, Web of knowledge, Scopus, and Google Scholar in May 2018. Joanna Briggs Institute (JBI) checklists was used for assessing the quality of the included articles. Results: The literature searches yielded 326 potentially relevant studies from the primary searches. Overall, the review included 10 unique studies. The results of this study showed that the area under curve (AUC) for the ANN was 0.91, (95% CI 0.89–0.83) and 0.89, (95% CI 0.87–90) for the LR in random effect model. The accuracy rate for ANN and LR in random effect models were 90.5, (95% CI, 87.6–94.2) and 83.2, (95% CI 75.1–91.2), respectively. Conclusion: The results of our study showed that ANN has better performance than LR in predicting the terminal outcomes of traumatic patients in both the AUC and accuracy rate. Using an ANN to predict the final implications of trauma patients can provide more accurate clinical decisions.

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مرتضی عرب زوزنیسوم

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