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Meningoencephalitis Diagnosis Using Contemporary Diagnostic Advancements
Afsona Parveen1, Prithviraj Karak2, Mrinal Acharya3
1Department of Bachelor in Medical Laboratory Technology, Durgapur Institute of Paramedical Science, Durgapur, West Bengal, India.
Neurology India
|July 24, 2025
Summary
Artificial intelligence (AI) and machine learning (ML) are improving meningoencephalitis diagnosis and risk assessment. These technologies enhance clinical processes, leading to better patient outcomes and resource efficiency in healthcare.
Area of Science:
- Medical Informatics
- Computational Biology
- Neurology
Background:
- Artificial intelligence (AI) and machine learning (ML) are increasingly utilized in healthcare.
- These technologies offer potential for improving diagnostic accuracy and efficiency.
- Meningoencephalitis diagnosis and management present challenges that may benefit from AI/ML applications.
Purpose of the Study:
- To evaluate the predictive and diagnostic potential of AI and ML algorithms for meningoencephalitis.
- To systematically review and meta-analyze existing studies on AI/ML in meningoencephalitis diagnosis and prediction.
Main Methods:
- Systematic review and meta-analysis of studies from Embase, ScienceDirect, PubMed, Web of Science, and Medline.
- PRISMA flow chart used for study selection and data extraction.
- Inclusion criteria focused on English-language studies concerning AI/ML for meningitis diagnosis and prediction.
Main Results:
- 34 studies were selected for assessment after screening 14,366 data points from an initial pool of 309,995 papers.
- AI and ML were found to enhance meningoencephalitis diagnosis, risk assessment, and resource efficiency.
- The selected studies were published between 2016 and 2024, with a notable increase in recent years.
Conclusions:
- AI and ML significantly enhance clinical processes and decentralization in healthcare.
- These technologies improve the diagnosis, risk assessment, and resource efficiency for meningoencephalitis.
- Future research should explore advanced diagnostics and further meta-analyses in this domain.
