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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 118
Article Submitted : 21470
Article Published : 8508
Total Authors : 22383
Total Reviewer : 805
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| Paper Title: | Early Detection of Chronic Obstructive Pulmonary Disease Using Boosting Algorithms |
| Authors Name: | P. Kamakshi , P. Vasu Pranusha , Md. Azra Tarannum , T. Nagasree , P. Harshith |
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IJRTI_189699
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| Published Paper Id: | IJRTI2404109 |
| Published In: | Volume 9 Issue 4, April-2024 |
| DOI: | |
| Abstract: | Globally, chronic obstructive pulmonary disease (COPD) is the third most common cause of death from lung disease. Although there isn't a known treatment for COPD, symptoms can be effectively managed and the disease's progression slowed down with prompt detection and individualized care. In this study, we present a machine learning-based method to identify the severity phases of COPD using two algorithms: XGBOOST and LIGHTGBM. We divided the severity into six categories—No COPD, Very low, Mild, Moderate, Severe, and Very Severe—are used to classify the various phases of the disease. We have used a dataset (5747 samples with 28 attributes) from the COPDGENE research study for our analysis. In order to assess the model's performance in predicting the severity stages of COPD, we used a variety of features during training and testing. With the XGBOOST algorithm obtaining 99.8% accuracy and the LIGHT GBM algorithm achieving 99.9% accuracy, the results show that the trained models obtained great accuracy. These results demonstrate the potential effectiveness of our strategy in the early detection and tailored treatment of COPD, improving patient outcomes and lowering medical costs in the process. |
| Keywords: | LIGHT GBM, XGBOOST, COPD (Chronic Obstructive Pulmonary Disease), Early Detection, Personalized Management. |
| Cite Article: | "Early Detection of Chronic Obstructive Pulmonary Disease Using Boosting Algorithms", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.9, Issue 4, page no.787 - 793, April-2024, Available :http://www.ijrti.org/papers/IJRTI2404109.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 |
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Published Paper ID: IJRTI2404109
Registration ID:189699
Published In: Volume 9 Issue 4, April-2024
DOI (Digital Object Identifier):
Page No: 787 - 793 Country: Vijayawada, Andhra Pradesh, India Research Area: Information Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2404109 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2404109 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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