A novel multimodal fusion framework for early diagnosis and accurate classification of COVID-19 patients using X-ray images and speech signal processing techniques.
- DOI
- 10.1016/j.cmpb.2022.107109
- Published
- 2022 Nov
- Container
- Computer methods and programs in biomedicine
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1016/j.cmpb.2022.107109,
title = {A novel multimodal fusion framework for early diagnosis and accurate classification of COVID-19 patients using X-ray images and speech signal processing techniques.},
author = {Kumar S and Chaube MK and Alsamhi SH and Gupta SK and Guizani M and Gravina R and Fortino G},
year = {2022},
journal = {Computer methods and programs in biomedicine},
doi = {10.1016/j.cmpb.2022.107109},
url = {https://doi.org/10.1016/j.cmpb.2022.107109}
}RIS
TY - JOUR TI - A novel multimodal fusion framework for early diagnosis and accurate classification of COVID-19 patients using X-ray images and speech signal processing techniques. AU - Kumar S AU - Chaube MK AU - Alsamhi SH AU - Gupta SK AU - Guizani M AU - Gravina R AU - Fortino G PY - 2022 JO - Computer methods and programs in biomedicine DO - 10.1016/j.cmpb.2022.107109 UR - https://doi.org/10.1016/j.cmpb.2022.107109 ER -
APA
S, K., MK, C., SH, A., SK, G., M, G., R, G., & G, F. (2022). A novel multimodal fusion framework for early diagnosis and accurate classification of COVID-19 patients using X-ray images and speech signal processing techniques.. Computer methods and programs in biomedicine. https://doi.org/10.1016/j.cmpb.2022.107109
Source records
- pubmed · retrieved 2026-09-25T03:26:11.810Z
- europe-pmc · retrieved 2026-09-25T03:26:11.827Z