Pennisi, F.; Pinto, A.; Cozzolino, C.; Cozza, A.; Rezza, G.; Signorelli, C.; Baldo, V.; Gianfredi, V.
Comparative Diagnostic Performance of Artificial Intelligence Versus Conventional Approaches for Early Detection of Mosquito-Borne Viral Infections: A Systematic Review and Meta-Analysis, with Evidence Predominantly from Dengue Studies. Mach. Learn. Knowl. Extr. 2026, 8, 93.
https://doi.org/10.3390/make8040093
AMA Style
Pennisi F, Pinto A, Cozzolino C, Cozza A, Rezza G, Signorelli C, Baldo V, Gianfredi V.
Comparative Diagnostic Performance of Artificial Intelligence Versus Conventional Approaches for Early Detection of Mosquito-Borne Viral Infections: A Systematic Review and Meta-Analysis, with Evidence Predominantly from Dengue Studies. Machine Learning and Knowledge Extraction. 2026; 8(4):93.
https://doi.org/10.3390/make8040093
Chicago/Turabian Style
Pennisi, Flavia, Antonio Pinto, Claudia Cozzolino, Andrea Cozza, Giovanni Rezza, Carlo Signorelli, Vincenzo Baldo, and Vincenza Gianfredi.
2026. "Comparative Diagnostic Performance of Artificial Intelligence Versus Conventional Approaches for Early Detection of Mosquito-Borne Viral Infections: A Systematic Review and Meta-Analysis, with Evidence Predominantly from Dengue Studies" Machine Learning and Knowledge Extraction 8, no. 4: 93.
https://doi.org/10.3390/make8040093
APA Style
Pennisi, F., Pinto, A., Cozzolino, C., Cozza, A., Rezza, G., Signorelli, C., Baldo, V., & Gianfredi, V.
(2026). Comparative Diagnostic Performance of Artificial Intelligence Versus Conventional Approaches for Early Detection of Mosquito-Borne Viral Infections: A Systematic Review and Meta-Analysis, with Evidence Predominantly from Dengue Studies. Machine Learning and Knowledge Extraction, 8(4), 93.
https://doi.org/10.3390/make8040093
