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40 articles for “Lung Cancer”
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Research ArticleOpen accessPhrase in the titleLung Cancer Detection Using Regularized Extreme Learning Machine and PCA FeaturesK. Kavitha, Dr. V. Saravana Kumar, V. Bhoopathy et al.When finding abnormalities in target images is time-sensitive, as it is with many cancer tumors, image processing techniques have recently found widespread use across various medical industries to improve images for early detection and treatment stages. In the setting of cancer, where time is of the essence in detecting anomalies within medical imaging, our research takes on further urgency. In … …Journal of Computer Science, Vol. 20, Issue 10 · 5 Aug 2024 · 5,302 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleAuto Weight Dilated Convolutional Ensemble Network for the Severity Analysis of Lung Cancer in CT ImagesL. Sandhya, K. MarimuthuLung cancer is one of the world's leading causes of morbidity and mortality; improving patient outcomes requires an early and precise diagnosis. Lesion and tumor segmentation remains a challenging task in CT images due to their inherent imaging limitations, such as the small size of nodules, heterogeneous textures, blurry boundaries, and adjacent structures, leading to misclassification and difficulty in delineating … …Journal of Computer Science, Vol. 22, Issue 1 · 9 Feb 2026 · 1,541 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA Computer Aided Diagnosis System for Lung Cancer Detection\Using Support Vector MachineM. Gomathi, P. ThangarajProblem statement: Computer Tomography (CT) has been considered as the most sensitive imaging technique for early detection of lung cancer. Approach: On the other hand, there is a requirement for automated methodology to make use of large amount of data obtained CT images. Computer Aided Diagnosis (CAD) can be used efficiently for early detection of Lung Cancer. Results: The usage … …American Journal of Applied Sciences, Vol. 7, Issue 12 · 31 Dec 2010 · 8,285 accessesView PDFCite
Research ArticleOpen accessIn the keywordsQuantitative Analysis of Hypothalamic Proline-Rich Peptide-1 in Blood Serum of Patients with Malignant TumorsNarine Tumasyan, Silva Abrahamyan, Nune Kocharyan et al.The proline-rich-peptides are a class of neurosecretory hypothalamic bioactive polypeptides derived from cattle and comprise the content of bovine posterior pituitary neurosecretory granules. These peptides are co-validated through a single precursor protein neurophysin-vasopressin-associated glycoprotein. Proline-Rich-Polypeptide-1 (PRP-1) is a 15-amino acid peptide with anti-neurodegenerative, immunoregulatory, hematopoietic, antimicrobial, and antitumor activity. The aim of this study, accordingly, is to elaborate an assay … …OnLine Journal of Biological Sciences, Vol. 25, Issue 4 · 27 Nov 2025 · 2,283 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEnhanced Support Vector Machine based on Metaheuristic Search for Multiclass ProblemsAbdullah Saeed Ghareb, Mohammed Hamid Afif, Abdel-Rahman Hedar et al.Machine learning is an important field of artificial intelligent researches and it highly growing for real intelligent applications systems that relate brain computer interface to human brain activities. Support Vector Machine (SVM) is a popular machine learning approach, which can be used for pattern recognition, prediction and classification with many diverse applications. However, the SVM has many parameters, which have … …Journal of Computer Science, Vol. 16, Issue 7 · 9 Jul 2020 · 6,906 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDetection of Pulmonary Nodules in ct Images Using Deep Learning TechniqueSanthi Balachandran, Divya, Nithya Rajendran, Brindha GiriLung Cancer is one of the most deadly diseases worldwide. According to the American Cancer Society, about 234,030 peoples have been suffering from lung cancer. It can be cured if it is diagnosed earlier which decreases the death rate. A computational diagnostic tool named Computer Aided Diagnosis (CAD) is used to detect pulmonary nodules. Extensive work has been made in … …Journal of Computer Science, Vol. 16, Issue 4 · 15 Apr 2020 · 7,816 accessesView PDFCite
Research ArticleOpen accessIn the keywordsClassification of Normal and Abnormal Lung CT-scan Images Using Cellular Learning AutomataNooshin Hadavi, Md Jan Nordin, Ali Shojaeipour, Mohammad Faidzul NasrudinThis paper proposes a medical pattern recognition system based on the Cellular automata (CA). CA or cellular machine is a dynamic mathematical model that consists of several similar and simple units organized by considerably simple local rules. Each cell acts as a simple computer automaton. This can lead to the implementation of the complex computations through uncomplicated methods. However, the … …Journal of Computer Science, Vol. 16, Issue 1 · 15 Jan 2020 · 7,834 accessesView PDFCite
Research ArticleOpen accessIn the keywordsChronic Lung Disease Identification in Chest CT Scans Through Hybrid Deep Transfer Learning FrameworkGarima Jain, Amit Kumar Goel, Rahul KumarAccurate and timely diagnosis is essential for successful treatment of chronic pulmonary conditions, particularly lung tumours. To capture more complicated pathological characteristics, diagnostic algorithms based on current data sets are restricted to using older databases and single branch systems. This research introduces a new solution: A hybrid deep learning model applied to a recently released quantitative database of CT scans … …Journal of Computer Science, Vol. 22, Issue 8 · 9 Sep 2026 · 651 accessesView PDFCite
Research ArticleOpen accessIn the abstractRefining Chest X-ray Interpretation with Deep Transfer Learning TechniquesR. Sriramkumar, K. Selvakumar, J. JeganChest X-rays are essential diagnostic tools for thoracic diseases, but different doctors' interpretations can differ greatly, which frequently results in inconsistent diagnoses. By using deep transfer learning techniques, this study seeks to improve the accuracy of Chest X-ray interpretations. More accurate and effective analysis can be accomplished with the growing potential of artificial intelligence (AI) in medical imaging, especially through … …Journal of Computer Science, Vol. 21, Issue 10 · 27 Nov 2025 · 2,644 accessesView PDFCite
Research ArticleOpen accessIn the abstractCytotoxicity and Apoptosis Prevailed by Tricyclohexyltin(IV) Dithiocarbamate Compounds Against Human Lung Carcinoma Cell Line (A549)Normah Awang, Nurul Amalina Abd Aziz, Nur Fatini Nordin, Nurul Farahana KamaludinIn Malaysia, lung cancer is a highly common kind of cancer and the leading cause of cancer-related deaths. This study examined the cytotoxicity of two new tricyclohexyltin(IV) dithiocarbamate compounds compounds, which are tricyclohexyltin(IV) N-methyl-N-benzyldithiocarbamate (C1) and tricyclohexyltin(IV) N-ethyl-N-benzyldithiocarbamate (C2), on lung carcinoma cell lines (A549) of humans. The cytotoxicity was assessed using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-tetrazolium bromide (MTT) assay. Cell death mode … …OnLine Journal of Biological Sciences, Vol. 24, Issue 4 · 13 Jun 2024 · 4,622 accessesView PDFCite