An insight into classifying viral and bacterial pneumonia on chest x-rays
DOI:
https://doi.org/10.59681/2175-4411.v16.iEspecial.2024.1341Keywords:
Artificial Intelligence, Chest X-rays, PneumoniaAbstract
Objective: This study presents a systematic review of the use of Artificial Intelligence (AI), especially Deep Learning (DL), in the diagnosis and classification of pneumonia using chest X-rays (CXR). Method: The study follows the PRISMA protocol, conducting a phased review of identification, screening, and analysis of articles from the Scopus database. Results: The review retrieved 25 relevant articles among 121 returned and identified growing scientific interest in the topic, in addition to advances in diagnosis, with some studies reaching up to 99.7% accuracy in the proposed model. Conclusion: Early detection of pneumonia is essential for more effective treatment, and solutions that help specialists are crucial. The literature shows that these solutions constantly evolve, although bottlenecks must be resolved.
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