Detecting Multi Thoracic Diseases in Chest X-Ray Images Using Deep Learning Techniques

被引：1
作者：
Quevedo, Sebastian [1 ,2 ]
Dominguez, Federico [1 ]
Pelaez, Enrique [1 ]
机构：
[1] Escuela Super Politecn Litoral ESPOL Univ, Elect & Comp Sci Engn Dept, Campus Gustavo Galindo km 30-5 Via Perimetral, Guayaquil, Ecuador
[2] Univ Catolica Cuenca, Cuenca, Ecuador
来源：
2023 IEEE 13TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION SYSTEMS, ICPRS | 2023年
关键词：
D O I：
10.1109/ICPRS58416.2023.10179041
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This doctoral proposal introduces a novel method for detecting and diagnosing various thoracic diseases in chest images using advanced deep-learning approaches. The research aims to establish a powerful and effective technique for promptly recognizing multiple pathologies in chest radiographs, which holds significant implications for patient outcomes and healthcare resources. Additionally, the study investigates the potential benefits of data augmentation, transfer learning strategies, and multimodal data integration to enhance the proposed approach's performance and adaptability.
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页数：7
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