Leveraging Machine Learning for Early Detection of Lung Diseases

Bahareh Rahmani, Harsha Reddy Bindela, Rama Kanth Reddy Gosula, Krishna Yedubati, Mohammad Amir Salari +4 more
12/27/2025
eess.IVcs.AIcs.CV

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Abstract

A combination of traditional image processing methods with advanced neural networks concretes a predictive and preventive healthcare paradigm. This study offers rapid, accurate, and non-invasive diagnostic solutions that can significantly impact patient outcomes, particularly in areas with limited access to radiologists and healthcare resources. In this project, deep learning methods apply in enhancing the diagnosis of respiratory diseases such as COVID-19, lung cancer, and pneumonia from chest x-rays. We trained and validated various neural network models, including CNNs, VGG16, InceptionV3, and EfficientNetB0, with high accuracy, precision, recall, and F1 scores to highlight the models' reliability and potential in real-world diagnostic applications.

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Cite this paper

@article{rahmani2025leveraging,
  title  = {Leveraging Machine Learning for Early Detection of Lung Diseases},
  author = {Bahareh Rahmani and Harsha Reddy Bindela and Rama Kanth Reddy Gosula and Krishna Yedubati and Mohammad Amir Salari and Leslie Hinyard and Payam Norouzzadeh and Eli Snir and Martin Schoen},
  year   = {2025},
  eprint = {2512.23757},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2512.23757v1}
}

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