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  • The Use of Neural Network Analysis of Digital X-ray Studies of the Chest Organs (Fluorography) for the Diagnosis of Lung Pathologies Using Computer Vision Technology

The Use of Neural Network Analysis of Digital X-ray Studies of the Chest Organs (Fluorography) for the Diagnosis of Lung Pathologies Using Computer Vision Technology

Student: David Kocharyan

Supervisor: Sergey A. Aksenov

Faculty: HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE)

Educational Programme: Applied Mathematics (Bachelor)

Final Grade: 9

Year of Graduation: 2024

Pneumonia — a severe respiratory illness often complicating viral infections such as COVID-19 or influenza. Timely diagnosis is crucial in its management, where neural networks analyzing radiographs can be instrumental. This process can be automated using computer vision methods. This study explores various algorithms for binary classification tasks concerning pneumonia presence on radiographs. While numerous articles have trained computer vision models for this task, most have utilized fewer than 2000 images for training, which does not guarantee result accuracy. To validate results and enhance the predictive capabilities of neural networks, this research trains the majority of models on existing data with an initial volume of approximately 6,000 images, expanded in this work to approximately 23,000 images.

Full text (added May 19, 2024)

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