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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14

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Paper Title: Lung Pulmonary Disease Detection And Classification Using Machine Learning Techniques
Authors Name: Srushti B Ingaleshwar , Pallavi Patil , Shreya Kirangi , Sonakshi Godbole
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IJRTI_204627
Published Paper Id: IJRTI2506113
Published In: Volume 10 Issue 6, June-2025
DOI:
Abstract: Lung diseases are among the leading causes of morbidity and mortality worldwide, with early detection playing a critical role in improving patient outcomes. This paper presents a machine learning-based approach for the detection and classification of pulmonary diseases using medical imaging data, specifically chest X-rays and CT scans. The proposed system employs pre-processing techniques to enhance image quality, followed by the application of advanced algorithms such as Convolutional Neural Networks (CNNs) for feature extraction and classification. The study focuses on classifying multiple types of lung diseases, including pneumonia, tuberculosis, and lung cancer. Emphasis is placed on accuracy, sensitivity, and computational efficiency to ensure practical applicability in clinical settings. The system is trained and validated on publicly available medical datasets and demonstrates high performance compared to traditional diagnostic methods. This research also addresses challenges such as dataset imbalance, feature noise, and model interpretability. By integrating machine learning techniques into the diagnostic process, the proposed model aims to support healthcare professionals in making faster and more accurate decisions, particularly in resource-constrained environments.
Keywords: Machine Learning, Lung Disease Detection, Pulmonary Classification, Chest X-ray, CNN, Medical Imaging, Pneumonia, Tuberculosis, Lung Cancer, Diagnostic Support System, Healthcare AI.
Cite Article: "Lung Pulmonary Disease Detection And Classification Using Machine Learning Techniques ", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 6, page no.b92-b95, June-2025, Available :http://www.ijrti.org/papers/IJRTI2506113.pdf
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ISSN: 2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publication Details: Published Paper ID: IJRTI2506113
Registration ID:204627
Published In: Volume 10 Issue 6, June-2025
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Page No: b92-b95
Country: kalaburagi, karanataka, India
Research Area: Computer Engineering 
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2506113
Published Paper PDF: https://www.ijrti.org/papers/IJRTI2506113
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED, Journal Starting Year (ESTD) : 2016

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