Harnessing the Power of AI to Improve Detection, Monitoring, and Public Health Interventions for Japanese Encephalitis
Japanese Encephalitis (JE) is the leading cause of viral encephalitis in regions with endemic Japanese Encephalitis Virus (JEV) infections. Background/Objectives: The aim of this review is to consider the potential role of artificial intelligence (AI) to improve detection, monitoring and public heal...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-12-01
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| Series: | Biomedicines |
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| Online Access: | https://www.mdpi.com/2227-9059/13/1/42 |
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| author | Junhua Xiao Evie Kendal Faith A. A. Kwa |
| author_facet | Junhua Xiao Evie Kendal Faith A. A. Kwa |
| author_sort | Junhua Xiao |
| collection | DOAJ |
| description | Japanese Encephalitis (JE) is the leading cause of viral encephalitis in regions with endemic Japanese Encephalitis Virus (JEV) infections. Background/Objectives: The aim of this review is to consider the potential role of artificial intelligence (AI) to improve detection, monitoring and public health interventions for JE. Discussion: As climate change continues to impact mosquito population growth patterns, more regions will be affected by mosquito-borne diseases, including JE. Improving diagnosis and surveillance, while continuing preventive measures, such as widespread vaccination campaigns in endemic regions, will be essential to reduce morbidity and mortality associated with JEV. Conclusions: With careful integration, AI mathematical and mechanistic models could be useful tools for combating the growing threat of JEV infections globally. |
| format | Article |
| id | doaj-art-7122b5ecccd246968596097ced720ba9 |
| institution | Kabale University |
| issn | 2227-9059 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biomedicines |
| spelling | doaj-art-7122b5ecccd246968596097ced720ba92025-01-24T13:23:49ZengMDPI AGBiomedicines2227-90592024-12-011314210.3390/biomedicines13010042Harnessing the Power of AI to Improve Detection, Monitoring, and Public Health Interventions for Japanese EncephalitisJunhua Xiao0Evie Kendal1Faith A. A. Kwa2School of Health Sciences, Swinburne University of Technology, Hawthorn, VIC 3122, AustraliaSchool of Health Sciences, Swinburne University of Technology, Hawthorn, VIC 3122, AustraliaSchool of Health Sciences, Swinburne University of Technology, Hawthorn, VIC 3122, AustraliaJapanese Encephalitis (JE) is the leading cause of viral encephalitis in regions with endemic Japanese Encephalitis Virus (JEV) infections. Background/Objectives: The aim of this review is to consider the potential role of artificial intelligence (AI) to improve detection, monitoring and public health interventions for JE. Discussion: As climate change continues to impact mosquito population growth patterns, more regions will be affected by mosquito-borne diseases, including JE. Improving diagnosis and surveillance, while continuing preventive measures, such as widespread vaccination campaigns in endemic regions, will be essential to reduce morbidity and mortality associated with JEV. Conclusions: With careful integration, AI mathematical and mechanistic models could be useful tools for combating the growing threat of JEV infections globally.https://www.mdpi.com/2227-9059/13/1/42Japanese Encephalitis VirusJEVJapanese EncephalitisJEartificial intelligenceAI |
| spellingShingle | Junhua Xiao Evie Kendal Faith A. A. Kwa Harnessing the Power of AI to Improve Detection, Monitoring, and Public Health Interventions for Japanese Encephalitis Biomedicines Japanese Encephalitis Virus JEV Japanese Encephalitis JE artificial intelligence AI |
| title | Harnessing the Power of AI to Improve Detection, Monitoring, and Public Health Interventions for Japanese Encephalitis |
| title_full | Harnessing the Power of AI to Improve Detection, Monitoring, and Public Health Interventions for Japanese Encephalitis |
| title_fullStr | Harnessing the Power of AI to Improve Detection, Monitoring, and Public Health Interventions for Japanese Encephalitis |
| title_full_unstemmed | Harnessing the Power of AI to Improve Detection, Monitoring, and Public Health Interventions for Japanese Encephalitis |
| title_short | Harnessing the Power of AI to Improve Detection, Monitoring, and Public Health Interventions for Japanese Encephalitis |
| title_sort | harnessing the power of ai to improve detection monitoring and public health interventions for japanese encephalitis |
| topic | Japanese Encephalitis Virus JEV Japanese Encephalitis JE artificial intelligence AI |
| url | https://www.mdpi.com/2227-9059/13/1/42 |
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