Application of machine learning tools and integrated OMICS for screening and diagnosis of inborn errors of metabolism
-
Published:2023-05-03
Issue:5
Volume:19
Page:
-
ISSN:1573-3890
-
Container-title:Metabolomics
-
language:en
-
Short-container-title:Metabolomics
Author:
Usha Rani Ganni,Kadali Srilatha,Kurma Reddy Banka,Shaheena Dudekula,Naushad Shaik Mohammad
Publisher
Springer Science and Business Media LLC
Subject
Clinical Biochemistry,Biochemistry,Endocrinology, Diabetes and Metabolism
Reference19 articles.
1. Babu, R. P., Bishnupriya, G., Thushara, P. K., Alap, C., Cariappa, R., Annapoorani, & Viswanathan, K. (2015). Detection of glutaric acidemia type 1 in infants through tandem mass spectrometry. Molecular genetics and metabolism reports, 3, 75–79. 2. Baumgartner, C., Böhm, C., & Baumgartner, D. (2005). Modelling of classification rules on metabolic patterns including machine learning and expert knowledge. Journal of biomedical informatics, 38(2), 89–98. 3. Cavedon, C. T., Bourdoux, P., Mertens, K., Van Thi, H. V., Herremans, N., de Laet, C., & Goyens, P. (2005). Age-related variations in acylcarnitine and free carnitine concentrations measured by tandem mass spectrometry. Clinical chemistry, 51(4), 745–752. 4. Céspedes, N., Valencia, A., Echeverry, C. A., Arce-Plata, M. I., Colón, C., Castiñeiras, D. E., Hurtado, P. M., Cocho, J. A., Herrera, S., & Arévalo-Herrera, M. (2017). Reference values of amino acids, acylcarnitines and succinylacetone by tandem mass spectrometry for use in newborn screening in southwest Colombia. Colombia medica (Cali, Colombia), 48(3), 113–119. 5. Chen, W. H., Hsieh, S. L., Hsu, K. P., Chen, H. P., Su, X. Y., Tseng, Y. J., Chien, Y. H., Hwu, W. L., & Lai, F. (2013). Web-based newborn screening system for metabolic diseases: Machine learning versus clinicians. Journal of medical Internet research, 15(5), e98.
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
|
|