ArticleInternational journal of environmental research and public health2020
Comparing Logistic Regression Models with Alternative Machine Learning Methods to Predict the Risk of Drug Intoxication Mortality.
Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Machine learning vs. traditional logistic regression: predictive performance and risk factor identification for child nutritional outcome in Pakistan.BMC public health · 2025Article
- Prediction of QTc Prolongation in Acute Poisoning with Atypical Antipsychotics Using Machine Learning Techniques: A Study from Poison Control Center.Cardiovascular toxicology · 2025Article
- The Artificial Intelligence-Powered New Era in Pharmaceutical Research and Development: A Review.AAPS PharmSciTech · 2024Review
- Comparison of Machine Learning Algorithms for Heartbeat Detection Based on Accelerometric Signals Produced by a Smart Bed.Sensors (Basel, Switzerland) · 2024Article
- 'International journal of environmental research and public health · 2023Article
- A Catalogue of Machine Learning Algorithms for Healthcare Risk Predictions.Sensors (Basel, Switzerland) · 2022Article
- Web-Based Skin Cancer Assessment and Classification Using Machine Learning and Mobile Computerized Adaptive Testing in a Rasch Model: Development Study.JMIR medical informatics · 2022Article
- Prediction of postoperative cardiopulmonary complications after lung resection in a Chinese population: A machine learning-based study.Frontiers in oncology · 2022Article
- A Machine Learning Algorithm for Predicting the Risk of Developing to M1b Stage of Patients With Germ Cell Testicular Cancer.Frontiers in public health · 2022Article
- Machine learning risk prediction model for acute coronary syndrome and death from use of non-steroidal anti-inflammatory drugs in administrative data.Scientific reports · 2021Article
- Using Ultrasound-Based Multilayer Perceptron to Differentiate Early Breast Mucinous Cancer and its Subtypes From Fibroadenoma.Frontiers in oncology · 2021Article
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Authors and funding
2 authors.
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Abstract
(1) Medical research has shown an increasing interest in machine learning, permitting massive multivariate data analysis. Thus, we developed drug intoxication mortality prediction models, and compared machine learning models and traditional logistic regression. (2) Categorized as drug intoxication, 8,937 samples were extracted from the Korea Centers for Disease Control and Prevention (2008-2017). We trained, validated, and tested each model through data and compared their performance using three measures: Brier score, calibration slope, and calibration-in-the-large. (3) A chi-square test demonstrated that mortality risk statistically significantly differed according to severity, intent, toxic substance, age, and sex. The multilayer perceptron model (MLP) had the highest area under the curve (AUC), and lowest Brier score in training and validation phases, while the logistic regression model (LR) showed the highest AUC (0.827) and lowest Brier score (0.0307) in the testing phase. MLP also had the second-highest AUC (0.816) and second-lowest Brier score (0.003258) in the testing phase, demonstrating better performance than the decision-making tree model. (4) Given the complexity of choosing tuning parameters, LR proved competitive when using medical datasets, which require strict accuracy.
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