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• W4385655250 startingPage "2617" @default.
• W4385655250 abstract "One of the most common and deadly diseases in the world is lung cancer. Only early identification of lung cancer can increase a patient’s probability of survival. A frequently used modality for the screening and diagnosis of lung cancer is computed tomography (CT) imaging, which provides a detailed scan of the lung. In line with the advancement of computer-assisted systems, deep learning techniques have been extensively explored to help in interpreting the CT images for lung cancer identification. Hence, the goal of this review is to provide a detailed review of the deep learning techniques that were developed for screening and diagnosing lung cancer. This review covers an overview of deep learning (DL) techniques, the suggested DL techniques for lung cancer applications, and the novelties of the reviewed methods. This review focuses on two main methodologies of deep learning in screening and diagnosing lung cancer, which are classification and segmentation methodologies. The advantages and shortcomings of current deep learning models will also be discussed. The resultant analysis demonstrates that there is a significant potential for deep learning methods to provide precise and effective computer-assisted lung cancer screening and diagnosis using CT scans. At the end of this review, a list of potential future works regarding improving the application of deep learning is provided to spearhead the advancement of computer-assisted lung cancer diagnosis systems." @default.
• W4385655250 created "2023-08-09" @default.
• W4385655250 creator A5000255592 @default.
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• W4385655250 creator A5054106321 @default.
• W4385655250 creator A5079128754 @default.
• W4385655250 date "2023-08-08" @default.
• W4385655250 modified "2023-09-30" @default.
• W4385655250 title "A Review of Deep Learning Techniques for Lung Cancer Screening and Diagnosis Based on CT Images" @default.
• W4385655250 cites W130099911 @default.
• W4385655250 cites W1589632398 @default.
• W4385655250 cites W1913405807 @default.
• W4385655250 cites W1966847100 @default.
• W4385655250 cites W1986649315 @default.
• W4385655250 cites W1987109777 @default.
• W4385655250 cites W1988117153 @default.
• W4385655250 cites W1988672262 @default.
• W4385655250 cites W1997709301 @default.
• W4385655250 cites W2005098328 @default.
• W4385655250 cites W2011153539 @default.
• W4385655250 cites W2013465174 @default.
• W4385655250 cites W2018365847 @default.
• W4385655250 cites W2058794460 @default.
• W4385655250 cites W2063451897 @default.
• W4385655250 cites W2073179893 @default.
• W4385655250 cites W2081709843 @default.
• W4385655250 cites W2084202389 @default.
• W4385655250 cites W2092168252 @default.
• W4385655250 cites W2096091589 @default.
• W4385655250 cites W2108598243 @default.
• W4385655250 cites W2120085308 @default.
• W4385655250 cites W2129132813 @default.
• W4385655250 cites W2137159718 @default.
• W4385655250 cites W2140775860 @default.
• W4385655250 cites W2322371438 @default.
• W4385655250 cites W2373606074 @default.
• W4385655250 cites W2396074317 @default.
• W4385655250 cites W2423277228 @default.
• W4385655250 cites W2509434949 @default.
• W4385655250 cites W2524399695 @default.
• W4385655250 cites W2594525001 @default.
• W4385655250 cites W2598574140 @default.
• W4385655250 cites W2607444182 @default.
• W4385655250 cites W2607941059 @default.
• W4385655250 cites W2624881194 @default.
• W4385655250 cites W2734776202 @default.
• W4385655250 cites W2742679468 @default.
• W4385655250 cites W2756258573 @default.
• W4385655250 cites W2762854770 @default.
• W4385655250 cites W2791142503 @default.
• W4385655250 cites W2793954249 @default.
• W4385655250 cites W2794187429 @default.
• W4385655250 cites W2888848380 @default.
• W4385655250 cites W2889242407 @default.
• W4385655250 cites W2894319790 @default.
• W4385655250 cites W2897821359 @default.
• W4385655250 cites W2899393783 @default.
• W4385655250 cites W2899472973 @default.
• W4385655250 cites W2899504557 @default.
• W4385655250 cites W2903150666 @default.
• W4385655250 cites W2903220004 @default.
• W4385655250 cites W2904914291 @default.
• W4385655250 cites W2910202556 @default.
• W4385655250 cites W2910380368 @default.
• W4385655250 cites W2913961394 @default.
• W4385655250 cites W2919115771 @default.
• W4385655250 cites W2921157435 @default.
• W4385655250 cites W2922342825 @default.
• W4385655250 cites W2929868177 @default.
• W4385655250 cites W2933170392 @default.
• W4385655250 cites W2936111010 @default.
• W4385655250 cites W2937276882 @default.
• W4385655250 cites W2945759189 @default.
• W4385655250 cites W2946185430 @default.
• W4385655250 cites W2954214015 @default.
• W4385655250 cites W2957352479 @default.
• W4385655250 cites W2963313410 @default.
• W4385655250 cites W2979617155 @default.
• W4385655250 cites W2999417355 @default.
• W4385655250 cites W2999978966 @default.
• W4385655250 cites W3007131888 @default.
• W4385655250 cites W3021898219 @default.
• W4385655250 cites W3036995978 @default.
• W4385655250 cites W3037280868 @default.
• W4385655250 cites W3040240789 @default.
• W4385655250 cites W3047502985 @default.
• W4385655250 cites W3048579340 @default.
• W4385655250 cites W3098977020 @default.
• W4385655250 cites W3100523627 @default.
• W4385655250 cites W3110954991 @default.
• W4385655250 cites W3113939469 @default.
• W4385655250 cites W3128646645 @default.
• W4385655250 cites W3129415988 @default.
• W4385655250 cites W3129886765 @default.
• W4385655250 cites W3131937258 @default.
• W4385655250 cites W3154422954 @default.
• W4385655250 cites W3160056982 @default.
• W4385655250 cites W3165693204 @default.

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