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  • Open Access

    ARTICLE

    Enhancing Early Detection of Lung Cancer through Advanced Image Processing Techniques and Deep Learning Architectures for CT Scans

    Nahed Tawfik1,*, Heba M. Emara2, Walid El-Shafai3, Naglaa F. Soliman4, Abeer D. Algarni4, Fathi E. Abd El-Samie4

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 271-307, 2024, DOI:10.32604/cmc.2024.052404 - 15 October 2024

    Abstract Lung cancer remains a major concern in modern oncology due to its high mortality rates and multifaceted origins, including hereditary factors and various clinical changes. It stands as the deadliest type of cancer and a significant cause of cancer-related deaths globally. Early diagnosis enables healthcare providers to administer appropriate treatment measures promptly and accurately, leading to improved prognosis and higher survival rates. The significant increase in both the incidence and mortality rates of lung cancer, particularly its ranking as the second most prevalent cancer among women worldwide, underscores the need for comprehensive research into efficient… More >

  • Open Access

    ARTICLE

    Lung Cancer Detection Using Modified AlexNet Architecture and Support Vector Machine

    Iftikhar Naseer1,*, Tehreem Masood1, Sheeraz Akram1, Arfan Jaffar1, Muhammad Rashid2, Muhammad Amjad Iqbal3

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 2039-2054, 2023, DOI:10.32604/cmc.2023.032927 - 22 September 2022

    Abstract Lung cancer is the most dangerous and death-causing disease indicated by the presence of pulmonary nodules in the lung. It is mostly caused by the instinctive growth of cells in the lung. Lung nodule detection has a significant role in detecting and screening lung cancer in Computed tomography (CT) scan images. Early detection plays an important role in the survival rate and treatment of lung cancer patients. Moreover, pulmonary nodule classification techniques based on the convolutional neural network can be used for the accurate and efficient detection of lung cancer. This work proposed an automatic… More >

  • Open Access

    ARTICLE

    Optimal Deep Belief Network Based Lung Cancer Detection and Survival Rate Prediction

    Sindhuja Manickavasagam1,*, Poonkuzhali Sugumaran2

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 939-953, 2023, DOI:10.32604/csse.2023.030491 - 16 August 2022

    Abstract The combination of machine learning (ML) approaches in healthcare is a massive advantage designed at curing illness of millions of persons. Several efforts are used by researchers for detecting and providing primary phase insights as to cancer analysis. Lung cancer remained the essential source of disease connected mortality for both men as well as women and their frequency was increasing around the world. Lung disease is the unrestrained progress of irregular cells which begin off in one or both Lungs. The previous detection of cancer is not simpler procedure however if it can be detected,… More >

  • Open Access

    ARTICLE

    Novel Contiguous Cross Propagation Neural Network Built CAD for Lung Cancer

    A. Alice Blessie1,*, P. Ramesh2

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1467-1484, 2023, DOI:10.32604/csse.2023.025399 - 15 June 2022

    Abstract The present progress of visual-based detection of the diseased area of a malady plays an essential part in the medical field. In that case, the image processing is performed to improve the image data, wherein it inhibits unintended distortion of image features or it enhances further processing in various applications and fields. This helps to show better results especially for diagnosing diseases. Of late the early prediction of cancer is necessary to prevent disease-causing problems. This work is proposed to identify lung cancer using lung computed tomography (CT) scan images. It helps to identify cancer… More >

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