Inteligencia Artificial Aplicada con técnicas de Procesamiento de Lenguaje Natural y Machine Learning en el campo de la salud.
Artificial Intelligence (AI), Natural Language Processing (NLP) and Machine Learning (ML) have played a crucial role in the fight against the Covid-19 pandemic, providing valuable technological tools for the diagnosis, monitoring and control of the disease, implementing AI solutions to mitigate its...
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| Main Authors: | , , , |
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| Format: | Online |
| Sprog: | spansk |
| Udgivet: |
Editorial Grupo AEA
2026
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| Fag: | |
| Online adgang: | https://directory.doabooks.org/handle/20.500.12854/172238 |
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| Summary: | Artificial Intelligence (AI), Natural Language Processing (NLP) and Machine Learning (ML) have played a crucial role in the fight against the Covid-19 pandemic, providing valuable technological tools for the diagnosis, monitoring and control of the disease, implementing AI solutions to mitigate its effects. We propose the design of an ML model applying NLP techniques in text preprocessing in order to evaluate the effectiveness of data analysis in conversations of people infected with the SARS-CoV-2 coronavirus. Information was collected from social networks such as Twitter and Facebook, and surveys of people infected with Covid-19 in Zone 8 of the province of Guayas. With these data, a textual classification system was trained using the Support Vector Machine and Random Forest algorithms. The study resulted in an accuracy of 96% in both models, demonstrating their viability for the creation and implementation of text classifiers. Model performance was improved by reducing categories with more than 200 occurrences, resulting in higher accuracy with no significant differences between the two models. Finally, a website capable of correctly classifying the symptoms and recommendations commented by patients was developed. |
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