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Linguistic methods in healthcare application and COVID-19 variants classification
Marek R Ogiela1, Urszula Ogiela2
1Cryptography and Cognitive Informatics Laboratory, AGH University of Science and Technology, 30 Mickiewicza Ave, 30-059 Kraków, Poland.
Neural Computing & Applications
|July 12, 2021
Summary
This study explores using mathematical linguistic methods for efficient coronavirus classification and medical data management. These AI-driven tools aid in distinguishing between different coronavirus variants for improved patient treatment.
Area of Science:
- Computational linguistics
- Medical informatics
- Infectious disease research
Background:
- Modern medicine prioritizes preventing pandemics and chronic diseases.
- Advanced IT and AI systems are crucial for patient diagnosis and treatment support.
- Coronavirus variants exhibit distinct RNA structures, leading to increased mutation and infection rates.
Purpose of the Study:
- To define efficient tools for coronavirus classification using mathematical linguistic methods.
- To present applications of linguistic techniques for managing medical data from coronavirus treatments.
- To explore classifying different coronavirus variants detected in patients.
Main Methods:
- Application of mathematical linguistic techniques.
- Analysis of medical data from coronavirus treatments.
- Development of AI-driven classification tools.
Main Results:
- Linguistic methods can effectively support the management of medical data related to coronavirus.
- AI tools can aid in classifying distinct coronavirus variants.
- Potential for improved patient stratification and treatment strategies.
Conclusions:
- Mathematical linguistics offers a promising approach for coronavirus variant classification.
- AI and IT infrastructure are vital for managing complex medical data in pandemic scenarios.
- Further research can enhance diagnostic and treatment capabilities for viral infections.
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