Support Vector Machine Outperforms Other Machine Learning Models in Early Diagnosis of Dengue Using Routine Clinical Data
Conclusion: Our study documents three circulating serotypes in the capital territory of Pakistan and highlights that the SVM outperformed other models, potentially serving as a valuable tool in clinical settings to aid in the rapid diagnosis of DF.
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-01-01
|
| Series: | Advances in Virology |
| Online Access: | http://dx.doi.org/10.1155/2024/5588127 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850106070781919232 |
|---|---|
| author | Ariba Qaiser Sobia Manzoor Asraf Hussain Hashmi Hasnain Javed Anam Zafar Javed Ashraf |
| author_facet | Ariba Qaiser Sobia Manzoor Asraf Hussain Hashmi Hasnain Javed Anam Zafar Javed Ashraf |
| author_sort | Ariba Qaiser |
| collection | DOAJ |
| description | Conclusion: Our study documents three circulating serotypes in the capital territory of Pakistan and highlights that the SVM outperformed other models, potentially serving as a valuable tool in clinical settings to aid in the rapid diagnosis of DF. |
| format | Article |
| id | doaj-art-319d20ebeb8b421b91a2f5ffca973fe7 |
| institution | OA Journals |
| issn | 1687-8647 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Virology |
| spelling | doaj-art-319d20ebeb8b421b91a2f5ffca973fe72025-08-20T02:38:55ZengWileyAdvances in Virology1687-86472024-01-01202410.1155/2024/5588127Support Vector Machine Outperforms Other Machine Learning Models in Early Diagnosis of Dengue Using Routine Clinical DataAriba Qaiser0Sobia Manzoor1Asraf Hussain Hashmi2Hasnain Javed3Anam Zafar4Javed Ashraf5Molecular Virology LabMolecular Virology LabInstitute of Biomedical and Genetic Engineering (IBGE)Provincial Public Health Reference LabDepartment of PediatricsDepartment of Community DentistryConclusion: Our study documents three circulating serotypes in the capital territory of Pakistan and highlights that the SVM outperformed other models, potentially serving as a valuable tool in clinical settings to aid in the rapid diagnosis of DF.http://dx.doi.org/10.1155/2024/5588127 |
| spellingShingle | Ariba Qaiser Sobia Manzoor Asraf Hussain Hashmi Hasnain Javed Anam Zafar Javed Ashraf Support Vector Machine Outperforms Other Machine Learning Models in Early Diagnosis of Dengue Using Routine Clinical Data Advances in Virology |
| title | Support Vector Machine Outperforms Other Machine Learning Models in Early Diagnosis of Dengue Using Routine Clinical Data |
| title_full | Support Vector Machine Outperforms Other Machine Learning Models in Early Diagnosis of Dengue Using Routine Clinical Data |
| title_fullStr | Support Vector Machine Outperforms Other Machine Learning Models in Early Diagnosis of Dengue Using Routine Clinical Data |
| title_full_unstemmed | Support Vector Machine Outperforms Other Machine Learning Models in Early Diagnosis of Dengue Using Routine Clinical Data |
| title_short | Support Vector Machine Outperforms Other Machine Learning Models in Early Diagnosis of Dengue Using Routine Clinical Data |
| title_sort | support vector machine outperforms other machine learning models in early diagnosis of dengue using routine clinical data |
| url | http://dx.doi.org/10.1155/2024/5588127 |
| work_keys_str_mv | AT aribaqaiser supportvectormachineoutperformsothermachinelearningmodelsinearlydiagnosisofdengueusingroutineclinicaldata AT sobiamanzoor supportvectormachineoutperformsothermachinelearningmodelsinearlydiagnosisofdengueusingroutineclinicaldata AT asrafhussainhashmi supportvectormachineoutperformsothermachinelearningmodelsinearlydiagnosisofdengueusingroutineclinicaldata AT hasnainjaved supportvectormachineoutperformsothermachinelearningmodelsinearlydiagnosisofdengueusingroutineclinicaldata AT anamzafar supportvectormachineoutperformsothermachinelearningmodelsinearlydiagnosisofdengueusingroutineclinicaldata AT javedashraf supportvectormachineoutperformsothermachinelearningmodelsinearlydiagnosisofdengueusingroutineclinicaldata |