ChromoCheck: Predicting Postnatal Chromosomal Trisomy Cases Using a Support Vector Machine Learning Model
Abstract
:1. Introduction
2. Methods
2.1. The Ethical Statement
2.2. Data Collection
2.3. Data Preprocessing
2.4. Training and Testing Support Vector Machine (SVM) Classifier
2.5. Classifier Evaluation Metrics
2.6. Web Deployment
2.7. Case Studies
3. Results
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
AI | Artificial Intelligence |
AFP | Alpha-Fetoprotein |
AUC | Area Under the Curve |
DS | Down Syndrome |
FN | False Negative |
FP | False Positive |
LOOCV | Leave-One-Out Cross-Validation |
ML | Machine Learning |
MODY | Maturity Onset Diabetes of the Young |
PCR | Polymerase Chain Reaction |
QF-PCR | Quantitative Fluorescent Polymerase Chain Reaction |
RF | Random Forest |
ROC | Receiver Operating Characteristic |
STR | Short Tandem Repeat |
SVM | Support Vector Machine |
T4 | Thyroxine Hormone |
TN | True Negative |
TP | True Positive |
TSH | Thyroid-Stimulating Hormone |
uE3 | Unconjugated Estriol |
kNN | k-Nearest Neighbor |
k-means | k-Means Clustering |
PHA | Phytohemagglutinin |
RPMI | Roswell Park Memorial Institute (medium for cell culture) |
EIA | Enzyme Immunoassay |
CRAN | Comprehensive R Archive Network |
CV | Cross-Validation |
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Average of Accuracy (%) | Average of Specificity (%) | Average of Sensitivity (%) | ||||
---|---|---|---|---|---|---|
Train | Test | Train | Test | Train | Test | |
Linear | 81% | 82% | 79% | 80% | 97% | 98% |
Radial | 77% | 79% | 75% | 77% | 96% | 95% |
Polynomial | 43% | 79% | 40% | 78% | 74% | 87% |
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© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
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Al-Mahrami, N.; Al Jabri, N.; Sallam, A.A.W.; Al Jahdhami, N.; Zadjali, F. ChromoCheck: Predicting Postnatal Chromosomal Trisomy Cases Using a Support Vector Machine Learning Model. Genes 2025, 16, 695. https://doi.org/10.3390/genes16060695
Al-Mahrami N, Al Jabri N, Sallam AAW, Al Jahdhami N, Zadjali F. ChromoCheck: Predicting Postnatal Chromosomal Trisomy Cases Using a Support Vector Machine Learning Model. Genes. 2025; 16(6):695. https://doi.org/10.3390/genes16060695
Chicago/Turabian StyleAl-Mahrami, Nabras, Nuha Al Jabri, Amal A. W. Sallam, Najwa Al Jahdhami, and Fahad Zadjali. 2025. "ChromoCheck: Predicting Postnatal Chromosomal Trisomy Cases Using a Support Vector Machine Learning Model" Genes 16, no. 6: 695. https://doi.org/10.3390/genes16060695
APA StyleAl-Mahrami, N., Al Jabri, N., Sallam, A. A. W., Al Jahdhami, N., & Zadjali, F. (2025). ChromoCheck: Predicting Postnatal Chromosomal Trisomy Cases Using a Support Vector Machine Learning Model. Genes, 16(6), 695. https://doi.org/10.3390/genes16060695