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Cancer is a life-threatening disease, which occurs due to genetic disorder and a variety of biochemical anomalies. Lung cancer along with colon cancer are two leading causes of fatalities in human beings. However, prior detection of the ailment can greatly lower the mortality rate. Deep learning methods can be employed to increase the rate of cancer detection. In this work, pretrained transfer learning model and ensemble learning with filtering for lung as well as colon cancer image datasets (LC25000) are used. From the study, it was observed that blended model can spot lung, colon, and both (lung + colon) cancer with an accuracy rate of 98.99, 99.84, and 99.24, respectively. This finding suggests that the proposed model performs better than the existing model. Therefore, these models can be useful in clinics to assist the medical practitioner in the identification of cancers.

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Comparative Analysis of Machine Learning Algorithms for Lung and Colon Cancer Classification Using Deep Feature Extraction

  • 章节

  • 发表日期：

    2025年

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  • Shalini Pradhan,
  • Suvasini Panigrahi

摘要

Cancer is a life-threatening disease, which occurs due to genetic disorder and a variety of biochemical anomalies. Lung cancer along with colon cancer are two leading causes of fatalities in human beings. However, prior detection of the ailment can greatly lower the mortality rate. Deep learning methods can be employed to increase the rate of cancer detection. In this work, pretrained transfer learning model and ensemble learning with filtering for lung as well as colon cancer image datasets (LC25000) are used. From the study, it was observed that blended model can spot lung, colon, and both (lung + colon) cancer with an accuracy rate of 98.99, 99.84, and 99.24, respectively. This finding suggests that the proposed model performs better than the existing model. Therefore, these models can be useful in clinics to assist the medical practitioner in the identification of cancers.