ArticleFrontiers in molecular biosciences2022
Random forest classifier improving phenylketonuria screening performance in two Chinese populations.
Article in Frontiers in molecular biosciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.
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13 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Accuracy of AI-based raman spectroscopy in the diagnosis of gastric cancer: a systematic review and meta-analysis.Lasers in medical science · 2026Pooled it
- The application of random forest-based models in prognostication of gastrointestinal tract malignancies: a systematic review.Frontiers in artificial intelligence · 2025Pooled it
- Development and testing of a random forest-based machine learning model for predicting events among breast cancer patients with a poor response to neoadjuvant chemotherapy.European journal of medical research · 2023Trial
- Assessing plague risk across seven decades of environmental change in Inner Mongolia, China: An interpretable machine learning.iScience · 2026Article
- Multicenter study of the diagnostic value of erythrocyte morphology assessment by the EH-2090 for differentiation of glomerular and non-glomerular hematuria.BMC nephrology · 2026Article
- Origin Identification ofMolecules (Basel, Switzerland) · 2026Article
- Article
- Effects of flour types and fermentation times on low-protein steamed buns.Food chemistry: X · 2025Article
- Associations Between Occupational Noise Exposure, Aging, and Gender and Hearing Loss: A Cross-Sectional Study in China.Audiology research · 2025Article
- The prognostic significance of epoxide hydrolases in colorectal cancer.Biochemistry and biophysics reports · 2025Article
- Prediction of non-suicidal self-injury (NSSI) among rural Chinese junior high school students: a machine learning approach.Annals of general psychiatry · 2024Article
- Improving methylmalonic acidemia (MMA) screening and MMA genotype prediction using random forest classifier in two Chinese populations.European journal of medical research · 2024Article
- Fast Label-Free Metabolic Profile Recognition Identifies Phenylketonuria and Subtypes.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
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Authors and funding
12 authors.
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Abstract
Phenylketonuria (PKU) is a genetic disorder with amino acid metabolic defect, which does great harms to the development of newborns and children. Early diagnosis and treatment can effectively prevent the disease progression. Here we developed a PKU screening model using random forest classifier (RFC) to improve PKU screening performance with excellent sensitivity, false positive rate (FPR) and positive predictive value (PPV) in all the validation dataset and two testing Chinese populations. RFC represented outstanding advantages comparing several different classification models based on machine learning and the traditional logistic regression model. RFC is promising to be applied to neonatal PKU screening.
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