PULMOCHECK: A Flask-Based Deep Learning System for Lung Health Screening

Lung illnesses such as tuberculosis and pneumonia remain significant global health risks, which is why early detection is critical to saving lives. To counter this, we created PULMOCHECK, a simple web application that uses machine learning to detect these illnesses from chest X-ray images. With the Flask framework, we created a system that integrates the strength of convolutional neural networks (CNNs) to detect diseases such as Tuberculosis, Pneumonia, and whether the lungs look Normal. The application also utilizes image segmentation to target lung regions, enhancing the accuracy of the diagnosis. Users can upload X-ray images, get instant results, and have their data securely stored in a MySQL database for easy retrieval. This tool is designed to make lung disease screening more accessible, particularly in locations where healthcare facilities are scarce, providing a fast and reliable means to assist doctors and patients in making informed treatment decisions.

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Publication Details

Published
2025-04-23
DOI
https://doi.org/10.1109/raeeucci63961.2025.11048318
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
Field-Weighted Citation Impact
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PULMOCHECK: A Flask-Based Deep Learning System for Lung Health Screening

M. Aakash, M. Parthiban, S. Sivasaravana Babu, Vinay Kumar et al.
Air Quality Monitoring and Forecasting
article

PULMOCHECK: A Flask-Based Deep Learning System for Lung Health Screening

M. Aakash, M. Parthiban, S. Sivasaravana Babu, Vinay Kumar, S. Bharathi, B. Arunkumar
article en

Abstract

Lung illnesses such as tuberculosis and pneumonia remain significant global health risks, which is why early detection is critical to saving lives. To counter this, we created PULMOCHECK, a simple web application that uses machine learning to detect these illnesses from chest X-ray images. With the Flask framework, we created a system that integrates the strength of convolutional neural networks (CNNs) to detect diseases such as Tuberculosis, Pneumonia, and whether the lungs look Normal. The application also utilizes image segmentation to target lung regions, enhancing the accuracy of the diagnosis. Users can upload X-ray images, get instant results, and have their data securely stored in a MySQL database for easy retrieval. This tool is designed to make lung disease screening more accessible, particularly in locations where healthcare facilities are scarce, providing a fast and reliable means to assist doctors and patients in making informed treatment decisions.

National Institute of Technology Meghalaya (IN)
Zero hunger
Openalex Percentile: Top 86%
Air Quality Monitoring and Forecasting
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