A study on the application and limitations of artificial intelligence in the treatment of lung cancer

Research Article
Open access

A study on the application and limitations of artificial intelligence in the treatment of lung cancer

Yuhao Zhou 1*
  • 1 High School Affiliated to The University of Nottingham Ningbo China, Ningbo, Zhejiang, 315048, China    
  • *corresponding author 13626812388@163.com
Published on 14 June 2023 | https://doi.org/10.54254/2755-2721/6/20230908
ACE Vol.6
ISSN (Print): 2755-273X
ISSN (Online): 2755-2721
ISBN (Print): 978-1-915371-59-1
ISBN (Online): 978-1-915371-60-7

Abstract

Lung cancer in China has the highest incidence rate and mortality rate. One reason is that it is difficult to make an early diagnosis. Artificial intelligence (AI) is a revolutionary technology rising at present. Combined with medical images and mechanical systems, it can diagnose and predict diseases through retrospective machine learning training of large sample cases. In this paper, the author studies the current application and limitations of AI in the medical treatment of lung cancer. Conclusions can be drawn that AI technology can be used for medical treatment because it has strong computing power and is more accurate than human beings. It can be used to operate some clinical operations that human beings cannot complete. Additionally, in order to achieve a comprehensive and standardized clinical application of AI in medical treatment, prospective, multi-center, and large sample studies are also needed to verify the robustness, accuracy, and generalization of the model.

Keywords:

Artificial intelligence, Lung cancer, Medical robot, Semi-automatic operation

Zhou,Y. (2023). A study on the application and limitations of artificial intelligence in the treatment of lung cancer. Applied and Computational Engineering,6,638-642.
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References

[1]. Fayaz, L., Bisma, B., Nahida, N. Applied artificial intelligence: A bibliometric study of an International Journal. COLLNET Journal of Scientometrics and Information Management 15, 27-45 (2021). 10.1080/09737766.2021.1938742.

[2]. Jiang, J., Lv, Z. M., Lv, F. J., Fu, B. J., Liang, Z. R., Chu, Z. G. Clinical and Computed Tomography Characteristics of Solitary Pulmonary Nodules Caused by Fungi: A Comparative Study. Infection and drug resistance 15, 6019-6028 (2022). https://doi.org/10.2147/IDR.S382289.

[3]. Callister, M. E., Baldwin, D. R. How should pulmonary nodules be optimally investigated and managed?. Lung cancer (Amsterdam, Netherlands) 91, 48-55 (2016). https://doi.org/10.1016/j.lungcan.2015.10.018.

[4]. Sverzellati, N., Calabró, E., Randi, G., la Vecchia, C., Marchianò, A.V., Kuhnigk, J., Zompatori, M., Spagnolo, P., Pastorino, U. Sex differences in emphysema phenotype in smokers without airflow obstruction. European Respiratory Journal 33, 1320-1328 (2009).

[5]. American Society of Clinical Oncology (ASCO). Lung Cancer - Non-Small Cell: Statistics. Approved by the Cancer.Net Editorial Board (2022). https://www.oncotarget.com/.

[6]. McNulty, W., Baldwin, D. Management of pulmonary nodules. BJR open 1(1), 20180051 (2019). https://doi.org/10.1259/bjro.20180051.

[7]. Dilger, S. K., Uthoff, J., Judisch, A., Hammond, E., Mott, S. L., Smith, B. J., Newell, J. D., Jr, Hoffman, E. A., Sieren, J. C. Improved pulmonary nodule classification utilizing quantitative lung parenchyma features. Journal of medical imaging (Bellingham, Wash.) 2(4), 041004 (2015). https://doi.org/10.1117/1.JMI.2.4.041004.

[8]. Huang, Y., Liu, Z., He, L., Chen, X., Pan, D., Ma, Z., Liang, C., Tian, J., Liang, C. Radiomics Signature: A Potential Biomarker for the Prediction of Disease-Free Survival in Early-Stage (I or II) Non-Small Cell Lung Cancer. Radiology 281(3), 947–957 (2016). https://doi.org/10.1148/radiol.2016152234.

[9]. Hawkins, S.H., Wang, H., Liu, Y., Garcia, A.L., Stringfield, O., Krewer, H., Li, Q., Cherezov, D., Gatenby, R.A., Balagurunathan, Y., Goldgof, D., Schabath, M.B., Hall, L.O., Gillies, R.J. Predicting Malignant Nodules from Screening CT Scans. Journal of Thoracic Oncology 11, 2120-2128 (2016).

[10]. Robotic Oncology. History and the future of Robotic Surgery. https://www.roboticoncology.com/history-of-robotic-surgery/#:~:text=In%202000%2C%20the%20da%20Vinci%20Surgery%20System%20broke,all-encompassing%20system%20of%20surgical%20instruments%20and%20camera%2Fscopic%20utensils.

Cite this article

Zhou,Y. (2023). A study on the application and limitations of artificial intelligence in the treatment of lung cancer. Applied and Computational Engineering,6,638-642.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 3rd International Conference on Signal Processing and Machine Learning

ISBN：978-1-915371-59-1(Print) / 978-1-915371-60-7(Online)
Editor：Omer Burak Istanbullu
Conference website: http://www.confspml.org
Conference date: 25 February 2023
Series: Applied and Computational Engineering
Volume number: Vol.6
ISSN：2755-2721(Print) / 2755-273X(Online)

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References

[1]. Fayaz, L., Bisma, B., Nahida, N. Applied artificial intelligence: A bibliometric study of an International Journal. COLLNET Journal of Scientometrics and Information Management 15, 27-45 (2021). 10.1080/09737766.2021.1938742.

[2]. Jiang, J., Lv, Z. M., Lv, F. J., Fu, B. J., Liang, Z. R., Chu, Z. G. Clinical and Computed Tomography Characteristics of Solitary Pulmonary Nodules Caused by Fungi: A Comparative Study. Infection and drug resistance 15, 6019-6028 (2022). https://doi.org/10.2147/IDR.S382289.

[3]. Callister, M. E., Baldwin, D. R. How should pulmonary nodules be optimally investigated and managed?. Lung cancer (Amsterdam, Netherlands) 91, 48-55 (2016). https://doi.org/10.1016/j.lungcan.2015.10.018.

[4]. Sverzellati, N., Calabró, E., Randi, G., la Vecchia, C., Marchianò, A.V., Kuhnigk, J., Zompatori, M., Spagnolo, P., Pastorino, U. Sex differences in emphysema phenotype in smokers without airflow obstruction. European Respiratory Journal 33, 1320-1328 (2009).

[5]. American Society of Clinical Oncology (ASCO). Lung Cancer - Non-Small Cell: Statistics. Approved by the Cancer.Net Editorial Board (2022). https://www.oncotarget.com/.

[6]. McNulty, W., Baldwin, D. Management of pulmonary nodules. BJR open 1(1), 20180051 (2019). https://doi.org/10.1259/bjro.20180051.

[7]. Dilger, S. K., Uthoff, J., Judisch, A., Hammond, E., Mott, S. L., Smith, B. J., Newell, J. D., Jr, Hoffman, E. A., Sieren, J. C. Improved pulmonary nodule classification utilizing quantitative lung parenchyma features. Journal of medical imaging (Bellingham, Wash.) 2(4), 041004 (2015). https://doi.org/10.1117/1.JMI.2.4.041004.

[8]. Huang, Y., Liu, Z., He, L., Chen, X., Pan, D., Ma, Z., Liang, C., Tian, J., Liang, C. Radiomics Signature: A Potential Biomarker for the Prediction of Disease-Free Survival in Early-Stage (I or II) Non-Small Cell Lung Cancer. Radiology 281(3), 947–957 (2016). https://doi.org/10.1148/radiol.2016152234.

[9]. Hawkins, S.H., Wang, H., Liu, Y., Garcia, A.L., Stringfield, O., Krewer, H., Li, Q., Cherezov, D., Gatenby, R.A., Balagurunathan, Y., Goldgof, D., Schabath, M.B., Hall, L.O., Gillies, R.J. Predicting Malignant Nodules from Screening CT Scans. Journal of Thoracic Oncology 11, 2120-2128 (2016).

[10]. Robotic Oncology. History and the future of Robotic Surgery. https://www.roboticoncology.com/history-of-robotic-surgery/#:~:text=In%202000%2C%20the%20da%20Vinci%20Surgery%20System%20broke,all-encompassing%20system%20of%20surgical%20instruments%20and%20camera%2Fscopic%20utensils.

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