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Artificial intelligence for lung cancer classification in cytology specimens: A systematic review and diagnostic test accuracy meta-analysis of benign-malignant diagnosis and ADC/SCC/SCLC subtyping. [PDF]
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Molecular Classification of Breast Cancer
PET Clinics, 2023Breast carcinomas classified based on traditional morphologic assessment provide useful prognostic information. Although morphology is still the gold standard of classification, recent advances in molecular technologies have enabled the classification of these tumors into four distinct subtypes based on its intrinsic molecular profile that provide both
Madhuchhanda, Roy +3 more
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Morphological classification of renal cancer
World Journal of Urology, 1995The current classification of renal-cell adenomas (RCAs) and carcinomas (RCCs) is based on eight basic cell and tumor types (entities) with characteristic morphologic features: (1) RCCs of clear-cell type, (2) RCAs/RCCs of chromophilic-cell type, (3) RCAs/RCCs of chromophobic-cell type, (4) RCCs of duct Bellini type, (5) RCCs of transitional-cell type,
STORKEL, S, VANDENBERG, E
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Classification of Pancreatic Cancer
Pancreas, 2004The Japan Pancreas Society (JPS) published the fifth Japanese edition of the General Rules for the Study of Pancreatic Cancer in 2002, the same year that the Union Internationale Contre le Cancer (UICC) published its sixth edition. The JPS fifth edition had been revised, based on data from 18,629 cases of carcinoma of the pancreas registered by the JPS
Shuji, Isaji +2 more
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Morphological classification of cancerous cells
Proceedings of 1st International Conference on Image Processing, 2002We present a new method for the automatic recognition of cancerous cells from a digitized picture of a microscopic section. The method is based on the analysis of four criteria of malignancy, in relation with the shape and the size of the observed cells.
Jean-Philippe Thiran +2 more
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Acta Anaesthesiologica Scandinavica, 1997
About three quarters of patients with advanced cancer experience pain. Most of these have multiple pains. Causes of pain fall into four broad categories: the cancer itself, related to the cancer +/‐ debility, related to treatment, concurrent disorder. From a neuropathological perspective, pain is either nociceptive or neuropathic.
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About three quarters of patients with advanced cancer experience pain. Most of these have multiple pains. Causes of pain fall into four broad categories: the cancer itself, related to the cancer +/‐ debility, related to treatment, concurrent disorder. From a neuropathological perspective, pain is either nociceptive or neuropathic.
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Refining the Classification of Field Cancerization
Dermatologic Surgery, 2023BACKGROUND Field cancerization is a commonly encountered but poorly defined entity in dermatology. Lack of a consensus definition makes characterizing and studying this condition difficult. OBJECTIVE Propose a framework for defining and managing field cancerization patients.
Bo, Kitrell +3 more
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The Classification of Cervical Cancer
Radiology, 1950As long as carcinoma of the cervix has been recognized and treated as such, a decided difference in the curability of this malignant process has been observed. Many factors of the disease have been explored in an endeavor to account for this disparity.
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Seminars in Roentgenology, 2011
o c T s The pathologic diagnosis of lung cancer is undergoing a remarkable transformation, largely driven by new therapies that are dependent on histologic type and/or molecular changes.1 Lung cancer is diagnosed pathologically by a histologic or cytologic approach.
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o c T s The pathologic diagnosis of lung cancer is undergoing a remarkable transformation, largely driven by new therapies that are dependent on histologic type and/or molecular changes.1 Lung cancer is diagnosed pathologically by a histologic or cytologic approach.
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Ensemble Classification for Cancer Data
2008 International Conference on BioMedical Engineering and Informatics, 2008Now the classification of different tumor types is of great importance in cancer diagnosis and drug discovery. It is more desirable to create an optimal ensemble for data analysis that deals with few samples and large features. In this paper, a new ensemble method for cancer data classification is proposed.
Yang Liu, Jin Zhou 0003, Yuehui Chen
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