Machine Learning Triage of LDLR Variants of Uncertain Significance Using Predictor Concordance and ACMG-Aligned Evidence Mapping
- DOI
- 10.3390/genes17091057
- Published
- 2026-08-31
- Container
- Genes
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/genes17091057,
title = {Machine Learning Triage of LDLR Variants of Uncertain Significance Using Predictor Concordance and ACMG-Aligned Evidence Mapping},
author = {BalaSubramani Gattu Linga and Faisal E. Ibrahim and Nader Al-Dewik},
year = {2026},
journal = {Genes},
doi = {10.3390/genes17091057},
url = {https://doi.org/10.3390/genes17091057}
}RIS
TY - JOUR TI - Machine Learning Triage of LDLR Variants of Uncertain Significance Using Predictor Concordance and ACMG-Aligned Evidence Mapping AU - BalaSubramani Gattu Linga AU - Faisal E. Ibrahim AU - Nader Al-Dewik PY - 2026 JO - Genes DO - 10.3390/genes17091057 UR - https://doi.org/10.3390/genes17091057 ER -
APA
Linga, B. G., Ibrahim, F. E., & Al-Dewik, N. (2026). Machine Learning Triage of LDLR Variants of Uncertain Significance Using Predictor Concordance and ACMG-Aligned Evidence Mapping. Genes. https://doi.org/10.3390/genes17091057
Source records
- crossref · retrieved 2026-09-26T18:18:39.097Z