Improving the Diagnosis of Phenylketonuria by Using a Machine Learning–Based Screening Model of Neonatal MRM Data-Reference-Cited by-同舟云学术

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Improving the Diagnosis of Phenylketonuria by Using a Machine Learning–Based Screening Model of Neonatal MRM Data

Published:2020-07-07 Issue: Volume:7 Page:
ISSN:2296-889X
Container-title:Frontiers in Molecular Biosciences
language:
Short-container-title:Front. Mol. Biosci.

Author:

Zhu Zhixing,Gu Jianlei,Genchev Georgi Z.,Cai Xiaoshu,Wang Yangmin,Guo Jing,Tian Guoli,Lu Hui

Publisher

Frontiers Media SA

Subject

Biochemistry, Genetics and Molecular Biology (miscellaneous),Molecular Biology,Biochemistry

Reference29 articles.

1. A tutorial on variable selection for clinical prediction models: feature selection methods in data mining could improve the results;Bagherzadeh-Khiabani;J. Clin. Epidemiol,2016

2. Classification on high dimensional metabolic data: phenylketonuria as an example;Baumgartner

3. Modelling of classification rules on metabolic patterns including machine learning and expert knowledge;Baumgartner;J. Biomed. Inform,2005

4. Supervised machine learning techniques for the classification of metabolic disorders in newborns;Baumgartner;Bioinformatics

5. Molecular genetics and diagnosis of phenylketonuria: state of the art;Blau;Expert Rev. Mol. Diagn,2014

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1. The significance of machine learning in neonatal screening for inherited metabolic diseases;Frontiers in Pediatrics;2024-03-20

2. Fast Label‐Free Metabolic Profile Recognition Identifies Phenylketonuria and Subtypes;Advanced Science;2024-02-13

3. Deep Learning and Explainable Artificial Intelligence for Improving Specificity and Detecting Metabolic Patterns in Newborn Screening;2023 IEEE Symposium Series on Computational Intelligence (SSCI);2023-12-05

4. Pediatrics in Artificial Intelligence Era: A Systematic Review on Challenges, Opportunities, and Explainability;Indian Pediatrics;2023-07

5. Machine Learning Methods Improve Specificity in Newborn Screening for Isovaleric Aciduria;Metabolites;2023-02-18

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