Lung Cancer Prediction Model to Improve Survival Rates
The truth that lung cancer is still the essential cause of cancer-related fatalities around the world emphasizes how critical early distinguishing proof is. This paper utilizes machine learning methods to reckon the chance of lung cancer from persistent information, such as socioeconomics, therap...
| Main Authors: | , |
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| Format: | Article |
| Language: | English English |
| Published: |
INTI International University
2024
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| Subjects: | |
| Online Access: | http://eprints.intimal.edu.my/2106/ http://eprints.intimal.edu.my/2106/2/644 http://eprints.intimal.edu.my/2106/3/joit2024_47b.pdf |
| _version_ | 1848766921720201216 |
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| author | Rakesh, Awati Manjula, Sanjay |
| author_facet | Rakesh, Awati Manjula, Sanjay |
| author_sort | Rakesh, Awati |
| building | INTI Institutional Repository |
| collection | Online Access |
| description | The truth that lung cancer is still the essential cause of cancer-related fatalities around the
world emphasizes how critical early distinguishing proof is. This paper utilizes machine
learning methods to reckon the chance of lung cancer from persistent information, such as
socioeconomics, therapeutic history, and imaging outcomes. The framework utilizes
calculations, counting calculated relapse, choice trees, and bolster vector machines, with the
objective of making strides in demonstrative accuracy and speeding up incite mediation. To
ensure the model's steadfastness in clinical settings, its execution is surveyed utilizing
measures counting exactness, exactness, and review. This strategy of treating lung cancer
has the potential to improve understanding results and early discovery rates. |
| first_indexed | 2025-11-14T11:58:50Z |
| format | Article |
| id | intimal-2106 |
| institution | INTI International University |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T11:58:50Z |
| publishDate | 2024 |
| publisher | INTI International University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | intimal-21062025-07-12T03:58:56Z http://eprints.intimal.edu.my/2106/ Lung Cancer Prediction Model to Improve Survival Rates Rakesh, Awati Manjula, Sanjay QA75 Electronic computers. Computer science QA76 Computer software RA Public aspects of medicine T Technology (General) The truth that lung cancer is still the essential cause of cancer-related fatalities around the world emphasizes how critical early distinguishing proof is. This paper utilizes machine learning methods to reckon the chance of lung cancer from persistent information, such as socioeconomics, therapeutic history, and imaging outcomes. The framework utilizes calculations, counting calculated relapse, choice trees, and bolster vector machines, with the objective of making strides in demonstrative accuracy and speeding up incite mediation. To ensure the model's steadfastness in clinical settings, its execution is surveyed utilizing measures counting exactness, exactness, and review. This strategy of treating lung cancer has the potential to improve understanding results and early discovery rates. INTI International University 2024-12 Article PeerReviewed text en cc_by_4 http://eprints.intimal.edu.my/2106/2/644 text en cc_by_4 http://eprints.intimal.edu.my/2106/3/joit2024_47b.pdf Rakesh, Awati and Manjula, Sanjay (2024) Lung Cancer Prediction Model to Improve Survival Rates. Journal of Innovation and Technology, 2024 (47). pp. 1-6. ISSN 2805-5179 http://ipublishing.intimal.edu.my/joint.html |
| spellingShingle | QA75 Electronic computers. Computer science QA76 Computer software RA Public aspects of medicine T Technology (General) Rakesh, Awati Manjula, Sanjay Lung Cancer Prediction Model to Improve Survival Rates |
| title | Lung Cancer Prediction Model to Improve Survival Rates |
| title_full | Lung Cancer Prediction Model to Improve Survival Rates |
| title_fullStr | Lung Cancer Prediction Model to Improve Survival Rates |
| title_full_unstemmed | Lung Cancer Prediction Model to Improve Survival Rates |
| title_short | Lung Cancer Prediction Model to Improve Survival Rates |
| title_sort | lung cancer prediction model to improve survival rates |
| topic | QA75 Electronic computers. Computer science QA76 Computer software RA Public aspects of medicine T Technology (General) |
| url | http://eprints.intimal.edu.my/2106/ http://eprints.intimal.edu.my/2106/ http://eprints.intimal.edu.my/2106/2/644 http://eprints.intimal.edu.my/2106/3/joit2024_47b.pdf |