International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Assistive System to Identify and Manage Lung Cancer

Abstract

Lung cancer, a leading cause of cancer-related deaths worldwide, necessitates early detection and effective management tools. This research introduces an assistive system leveraging machine learning to identify risk factors and prioritize treatments based on severity. Critical socio-demographic data, like age, gender, and smoking history, enable accurate risk assessment and personalized profiles. The system adapts to lifestyle changes post-diagnosis, offering tailored healthcare solutions. Integrating Mask R-CNN, a deep learning algorithm for medical imaging, enhances lung cancer diagnosis precision and treatment strategies. The user-friendly interface allows healthcare providers, caregivers, and patients easy access via mobile or computer applications. The implementation includes natural language processing for questionnaires and data preprocessing. The system's design consists of three components: front-end interface, back-end server, and Mask R-CNN for tumor identification. Correlation analysis for patient prioritization to generate a list. The proposed system aims to revolutionize lung cancer care, delivering accurate risk assessments, personalized treatment plans, and continuous monitoring, ultimately improving patient outcomes and saving lives.

Country : Sri Lanka

1 D.A.H.K. Rathnayaka2 E.M.V.Y. Ekanayake3 K.K. Paranavithana4 K.B.A.S.M. Dissanayake5 Wishalya Tissera6 6Dasuni Nawinna

  1. Department of Information Technology Sri Lanka Institute of Information Technology Malabe, Sri Lanka
  2. Department of Information Technology Sri Lanka Institute of Information Technology Malabe, Sri Lanka
  3. Department of Information Technology Sri Lanka Institute of Information Technology Malabe, Sri Lanka
  4. Department of Information Technology Sri Lanka Institute of Information Technology Malabe, Sri Lanka
  5. Department of Information Technology Sri Lanka Institute of Information Technology Malabe, Sri Lanka
  6. Department of Computer Systems Engineering Sri Lanka Institute of Information Technology Malabe, Sri Lanka

IRJIET, Volume 7, Issue 11, November 2023 pp. 79-86

doi.org/10.47001/IRJIET/2023.711011

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References

  1. Kunkler, I. H., Audisio, R., Belkacemi, Y., Betz, M., Gore, E., … Hoffe, S. (2014). Review of current best practice and priorities for research in radiation oncology for elderly patients with cancer: the International Society of Geriatric Oncology (SIOG) task force. Annals of Oncology, 25(11), 2134–2146. doi:10.1093/annonc/mdu104.
  2. Passaro, A., Addeo, A., Von Garnier, C., Blackhall, F., Planchard, D., Felip, E., Dziadziuszko, R., De Marinis, F., Reck, M., Bouchaab, H., & Peters, S. (2020, January 1). ESMO Management and treatment adapted recommendations in the COVID-19 era: Lung cancer. ESMO Open; Elsevier BV. https://doi.org/10.1136/esmoopen-2020-000820.
  3. Ellis J. The impact of lung cancer on patients and carers. Chron Respir Dis. 2012 Feb;9(1):39-47. doi: 10.1177/1479972311433577. PMID: 22308553.
  4. Polanski J, Jankowska-Polanska B, Rosinczuk J, Chabowski M, Szymanska-Chabowska A. Quality of life of patients with lung cancer. Onco Targets Ther. 2016 Feb 29;9:1023-8. doi: 10.2147/OTT.S100685. PMID: 27013895; PMCID: PMC4778772.
  5. Pompili C. Quality of life after lung resection for lung cancer. J Thorac Dis. 2015 Apr;7(Suppl 2):S138-44. doi: 10.3978/j.issn.2072-1439.2015.04.40. PMID: 25984359; PMCID: PMC4419027.
  6. M. Maambo, J. Phiri, M. Kalumbilo, and L. Jaganathan, “Assisted Artificial Intelligence Medical Diagnosis System for Heart Disease”, zictjournal, vol. 6, no. 1, pp. 38–43, Dec. 2022.
  7. Margaret R. Spitz, Carol J. Etzel, Qiong Dong, Christopher I. Amos, Qingyi Wei, Xifeng Wu, Waun Ki Hong; An Expanded Risk Prediction Model for Lung Cancer. Cancer Prev Res (Phila) 1 September 2008; 1 (4): 250–254. https://doi.org/10.1158/1940-6207.CAPR-08-0060.
  8. Muller DC, Johansson M, Brennan P. Lung Cancer Risk Prediction Model Incorporating Lung Function: Development and Validation in the UK Biobank Prospective Cohort Study. J Clin Oncol. 2017 Mar 10;35(8):861-869. doi: 10.1200/JCO.2016.69.2467. Epub 2017 Jan 17. PMID: 28095156.
  9. Dritsas, E. and Trigka, M. (2022) Lung cancer risk prediction with machine learning models, MDPI. Available at: https://www.mdpi.com/2504-2289/6/4/139.
  10. G. A. Singh and P. K. Gupta, “Performance analysis of various machine learning-based approaches for detection and classification of lung cancer in humans,” Neural Computing and Applications, vol. 31, no. 10, pp. 6863–6877, 2018. doi:10.1007/s00521-018-3518-x.
  11. Patra, R. (2020). Prediction of Lung Cancer Using Machine Learning Classifier. In: Chaubey, N., Parikh, S., Amin, K. (eds) Computing Science, Communication and Security. COMS2 2020. Communications in Computer and Information Science, vol 1235. Springer, Singapore. https://doi.org/10.1007/978-981-15-6648-6_11.
  12. S. Bhardwaj et al., “Detection and classification of lung cancer CT images using mask R-CNN based generated mask method,” 2023 1st International Conference on Innovations in High-Speed Communication and Signal Processing (IHCSP), 2023. doi:10.1109/ihcsp56702.2023.10127160.
  13. M. Liu, J. Dong, X. Dong, H. Yu, and L. Qi, "Segmentation of Lung Nodule in CT Images Based on Mask R-CNN," 2018 9th International Conference on Awareness Science and Technology (iCAST), Fukuoka, Japan, 2018, pp. 1-6, doi: 10.1109/ICAwST.2018.85.
  14. Ying Xie, Wei-Yu Meng, Run-Ze Li, Yu-Wei Wang, Xin Qian, Chang Chan, Zhi-Fang Yu, Xing-Xing Fan, Hu-Dan Pan, Chun Xie, Qi-Biao Wu, Pei-Yu Yan, Liang Liu, Yi-Jun Tang, Xiao-Jun Yao, Mei-Fang Wang, Elaine Lai-Han Leung, Early lung cancer diagnostic biomarker discovery by machine learning methods, Translational Oncology, Volume 14, Issue 1,2021,100907,ISSN 1936-5233,https://doi.org/10.1016/j.tranon.2020.100907.
  15. Sabina Asensio-Cuesta, Ángel Sánchez-García, Teresa Soria Comes, Inmaculada Maestu, Maria Martín Ureste, J. Alberto Conejero & Juan M. García-Gómez (2022) Testing Lung Cancer Patients’ and Oncologists’ Experience with the Lalaby App for Monitoring the Quality of Life through Mobile Sensors and Integrated Questionnaires, International Journal of Human–Computer Interaction, DOI: 10.1080/10447318.2022.2121561.
  16. R. P.R., R. A. S. Nair, and V. G., "A Comparative Study of Lung Cancer Detection using Machine Learning Algorithms," 2019 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT), Coimbatore, India, 2019, pp. 1-4, doi: 10.1109/ICECCT.2019.8869001.
  17. Lu, T. et al. (2019) ‘Trends in the incidence, treatment, and survival of patients with lung cancer in the last four decades’, Cancer Management and Research, Volume 11, pp. 943–953. doi:10.2147/cmar.s187317.
  18. TAS, F. et al. (2013) ‘Age is a prognostic factor affecting survival in lung cancer patients’, Oncology Letters, 6(5), pp. 1507–1513. doi:10.3892/ol.2013.1566.
  19. Pourhomayoun, M. and Shakibi, M. (2021) ‘Predicting mortality risk in patients with COVID-19 using machine learning to help medical decision-making’, Smart Health, 20, p. 100178. doi:10.1016/j.smhl.2020.100178.
  20. Wang, Y. et al. (2021) ‘A machine learning-based investigation of gender-specific prognosis of lung cancers’, Medicina, 57(2), p. 99. doi:10.3390/medicina57020099.
  21. Elcholiqi, Abidah & Musdholifah, Aina. (2020). Chatbot in Bahasa Indonesia using NLP to Provide Banking Information. IJCCS (Indonesian Journal of Computing and Cybernetics Systems). 14. 91. 10.22146/ijccs.41289.
  22. H. Yan, H. Lu, M. Ye, K. Yan, Y. Xu, and Q. Jin, "Improved Mask R-CNN for Lung Nodule Segmentation," 2019 10th International Conference on Information Technology in Medicine and Education (ITME), Qingdao, China, 2019, pp. 137-141, doi: 10.1109/ITME.2019.00041.Motorola Semiconductor Data Manual, Motorola Semiconductor Products Inc., Phoenix, AZ, USA, 1989.

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