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https://www.readbyqxmd.com/read/28231677/-a-systematic-review-of-worldwide-natural-history-models-of-colorectal-cancer-classification-transition-rate-and-a-recommendation-for-developing-chinese-population-specific-model
#1
Z F Li, H Y Huang, J F Shi, C G Guo, S M Zou, C C Liu, Y Wang, L Wang, S L Zhu, S L Wu, M Dai
Objective: To review the worldwide studies on natural history models among colorectal cancer (CRC), and to inform building a Chinese population-specific CRC model and developing a platform for further evaluation of CRC screening and other interventions in population in China. Methods: A structured literature search process was conducted in PubMed and the target publication dates were from January 1995 to December 2014. Information about classification systems on both colorectal cancer and precancer on corresponding transition rate, were extracted and summarized...
February 10, 2017: Zhonghua Liu Xing Bing Xue za Zhi, Zhonghua Liuxingbingxue Zazhi
https://www.readbyqxmd.com/read/28231672/-analysis-on-cancer-deaths-and-cause-eliminated-life-expectancy-among-residents-of-tianjin-2015
#2
Z L Xu, H Zhang, D Z Wang, G D Song, C F Shen, S Zhang, Y Zhang, G H Jiang
Objective: To explore the causes of cancer deaths and cause-eliminated-life-expectancy among residents of Tianjin. Methods: Data from the death registry system of Tianjin residents in 2015 were collected and cancers were grouped according to the classification of Global Burden of Disease. Specific cancer crude death rate and cause eliminated life expectancy (CELE) were calculated. Results: In 2015, 17 641 Tianjin residents died of cancer, with the crude death rate as 171.79 per 100 thousand and the standardized rate according to the Chinese population in 2000 as 86...
February 10, 2017: Zhonghua Liu Xing Bing Xue za Zhi, Zhonghua Liuxingbingxue Zazhi
https://www.readbyqxmd.com/read/28231559/prostate-cancer-heterogeneity-discovering-novel-molecular-targets-for-therapy
#3
REVIEW
Chiara Ciccarese, Francesco Massari, Roberto Iacovelli, Michelangelo Fiorentino, Rodolfo Montironi, Vincenzo Di Nunno, Francesca Giunchi, Matteo Brunelli, Giampaolo Tortora
Prostate cancer (PCa) shows a broad spectrum of biological and clinical behavior, which represents the epiphenomenon of an extreme genetic heterogeneity. Recent genomic profiling studies have deeply improved the knowledge of the genomic landscape of localized and metastatic PCa. The AR and PI3K/Akt/mTOR signaling pathways are the two most frequently altered, representing therefore interestingly targets for therapy. Moreover, somatic or germline aberrations of DNA repair genes (DRGs) have been observed at high frequency, supporting the potential role of platinum derivatives and PARP inhibitors as effective therapeutic strategies...
February 11, 2017: Cancer Treatment Reviews
https://www.readbyqxmd.com/read/28229187/-precursors-of-gastric-cancer-dysplasia-and-adenoma
#4
C Langner
Gastric cancer develops from preneoplastic and early neoplastic precursor lesions. In particular, the intestinal type according to the Lauren classification is driven by chronic inflammation and progresses via a chronic gastritis - atrophy/metaplasia - dysplasia - carcinoma sequence. Staging of the extent of atrophy (OLGA) or intestinal metaplasia (OLGIM) enables risk stratification and determines follow-up investigations according to the management of precancerous conditions and lesions in the stomach (MAPS) international guidelines...
February 22, 2017: Der Pathologe
https://www.readbyqxmd.com/read/28229027/risk-analysis-of-colorectal-cancer-incidence-by-gene-expression-analysis
#5
Wei-Chuan Shangkuan, Hung-Che Lin, Yu-Tien Chang, Chen-En Jian, Hueng-Chuen Fan, Kang-Hua Chen, Ya-Fang Liu, Huan-Ming Hsu, Hsiu-Ling Chou, Chung-Tay Yao, Chi-Ming Chu, Sui-Lung Su, Chi-Wen Chang
BACKGROUND: Colorectal cancer (CRC) is one of the leading cancers worldwide. Several studies have performed microarray data analyses for cancer classification and prognostic analyses. Microarray assays also enable the identification of gene signatures for molecular characterization and treatment prediction. OBJECTIVE: Microarray gene expression data from the online Gene Expression Omnibus (GEO) database were used to to distinguish colorectal cancer from normal colon tissue samples...
2017: PeerJ
https://www.readbyqxmd.com/read/28228225/-advances-in-classification-and-research-methods-of-lung-epithelial-stem-%C3%A2-and-progenitor-cells
#6
Minhua Deng, Jinhua Li, Ye Gan, Ping Chen
Isolation and characterization of lung epithelial stem and progenitor cells and understanding of their specific role in lung physiopathology are critical for preventing and controlling lung diseases including lung cancer. In this review, we summarized recent advances in classification and research methods of lung epithelial stem and progenitor cells. Lung epithelial stem and progenitor cells were region-specific, which primarily included basal cells and duct cells in proximal airway, Clara cells, variant Clara cells, bronchioalveolar stem cells and induced krt5+ cells in bronchioles, type II alveolar cells and type II alveolar progenitor cells in alveoli...
February 20, 2017: Zhongguo Fei Ai za Zhi, Chinese Journal of Lung Cancer
https://www.readbyqxmd.com/read/28228010/selective-fusion-of-heterogeneous-classifiers-for-predicting-substrates-of-membrane-transporters
#7
Naeem Shaikh, Mahesh Sharma, Prabha Garg
Membrane transporters play a crucial role in determining fate of administered drugs in a biological system. Early identification of plausible transporters for a drug molecule can provide insights into its therapeutic, pharmacokinetic and toxicological profile. In the present study, predictive models for classifying small molecules into substrates and non-substrates of various pharmaceutically important membrane transporters are developed using QSAR and proteochemometric (PCM) approaches. For this purpose, 4575 substrate interactions for these transporters were collected from Metabolism and Transport Database (Metrabase) and literature...
February 23, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28227670/diffuse-reflectance-spectroscopy-can-differentiate-high-grade-and-low-grade-prostatic-carcinoma
#8
Priya N Werahera, Edward A Jasion, E David Crawford, M Scott Lucia, Adrie van Bokhoven, Holly T Sullivan, Fernando J Kim, Paul D Maroni, J David Port, John W Daily, Francisco G La Rosa, Priya N Werahera, Edward A Jasion, E David Crawford, M Scott Lucia, Adrie van Bokhoven, Holly T Sullivan, Fernando J Kim, Paul D Maroni, J David Port, John W Daily, Francisco G La Rosa, John W Daily, Adrie Van Bokhoven, E David Crawford, J David Port, Priya N Werahera, M Scott Lucia, Holly T Sullivan, Paul D Maroni, Edward A Jasion, Francisco G La Rosa, Fernando J Kim
Prostate tumors are graded by the revised Gleason Score (GS) which is the sum of the two predominant Gleason grades present ranging from 6-10. GS 6 cancer exclusively with Gleason grade 3 is designated as low grade (LG) and correlates with better clinical prognosis for patients. GS >7 cancer with at least one of the Gleason grades 4 and 5 is designated as HG indicate worse prognosis for patients. Current transrectal ultrasound guided prostate biopsies often fail to correctly diagnose HG prostate cancer due to sampling errors...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227384/automatic-classification-of-cancer-cells-in-multispectral-microscopic-images-of-lymph-node-samples
#9
Gali Zimmerman-Moreno, Irina Marin, Moshe Lindner, Iris Barshack, Yuval Garini, Eli Konen, Arnaldo Mayer, Gali Zimmerman-Moreno, Irina Marin, Moshe Lindner, Iris Barshack, Yuval Garini, Eli Konen, Arnaldo Mayer, Moshe Lindner, Yuval Garini, Gali Zimmerman-Moreno, Arnaldo Mayer, Eli Konen, Iris Barshack, Irina Marin
Histopathological analysis is crucial for the diagnosis of a large number of cancer types. A lot of progress has been made in the development of molecular based assays, but many of the cases still require the careful analysis of the stained tissue under a bright-field microscope and its analysis. This procedure is costly and time-consuming. We present a novel method for classification of cancer cells in lymph node images. It is based on the measurement of the spectral image of hematoxylin and eosin stained sample under the microscope and the analysis of the acquired data using state of the art machine learning techniques...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227373/comparative-study-of-texture-features-in-oct-images-at-different-scales-for-human-breast-tissue-classification
#10
Yu Gan, Xinwen Yao, Ernest Chang, Syed Bin Amir, Hanina Hibshoosh, Sheldon Feldman, Christine P Hendon, Yu Gan, Xinwen Yao, Ernest Chang, Syed Bin Amir, Hanina Hibshoosh, Sheldon Feldman, Christine P Hendon, Syed Bin Amir, Christine P Hendon, Sheldon Feldman, Yu Gan, Hanina Hibshoosh, Ernest Chang, Xinwen Yao
Breast cancer is the second leading cause of death in women in the United States due to cancer. Early detection of breast cancerous regions will aid the diagnosis, staging, and treatment of breast cancer. Optical coherence tomography (OCT), a non-invasive imaging modality with high resolution, has been widely used to visualize various tissue types within the human breast and has demonstrated great potential for assessing tumor margins. Imaging large resected samples with a fast imaging speed can be accomplished by under-sampling in the spatial domain, resulting in a large image scale...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227169/biomarker-discovery-based-on-bbha-and-adaboostm1-on-microarray-data-for-cancer-classification
#11
Elnaz Pashaei, Mustafa Ozen, Nizamettin Aydin, Elnaz Pashaei, Mustafa Ozen, Nizamettin Aydin, Nizamettin Aydin, Elnaz Pashaei, Mustafa Ozen
In this paper, a new approach based on Binary Black Hole Algorithm (BBHA) and Adaptive Boosting version Ml (AdaboostM1) is proposed for finding genes that can classify the group of cancers correctly. In this approach, BBHA is used to perform gene selection and AdaboostM1 with 10-fold cross validation is adopted as the classifier. Also, to find the relation between the biomarkers for biological point of view, decision tree algorithm (C4.5) is utilized. The proposed approach is tested on three benchmark microarrays...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227121/automated-basal-cell-carcinoma-detection-in-high-definition-optical-coherence-tomography
#12
Annan Li, Jun Cheng, Ai Ping Yow, Ruchir Srivastava, Damon Wing Kee Wong, Hong Liang Tey, Jiang Liu, Annan Li, Jun Cheng, Ai Ping Yow, Ruchir Srivastava, Damon Wing Kee Wong, Hong Liang Tey, Jiang Liu, Ai Ping Yow, Jiang Liu, Annan Li, Hong Liang Tey, Jun Cheng, Ruchir Srivastava
Basal cell carcinoma (BCC) is the most common non-melanoma skin cancer. Conventional diagnosis of BCC requires invasive biopsies. Recently, a high-definition optical coherence tomography (HD-OCT) technique has been developed, which provides a non-invasive in vivo imaging method of skin. Good agreements of BCC features between HD-OCT images and histopathological architecture have been found. Therefore it is possible to automatically detect BCC using HD-OCT. This paper presents a novel BCC detection method that consists of four steps: graph based skin surface segmentation, surface flattening, deep feature extraction and the BCC classification...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227012/detection-of-mitotic-nuclei-in-breast-histopathology-images-using-localized-acm-and-random-kitchen-sink-based-classifier
#13
K Sabeena Beevi, Madhu S Nair, G R Bindu, K Sabeena Beevi, Madhu S Nair, G R Bindu, G R Bindu, Madhu S Nair
The exact measure of mitotic nuclei is a crucial parameter in breast cancer grading and prognosis. This can be achieved by improving the mitotic detection accuracy by careful design of segmentation and classification techniques. In this paper, segmentation of nuclei from breast histopathology images are carried out by Localized Active Contour Model (LACM) utilizing bio-inspired optimization techniques in the detection stage, in order to handle diffused intensities present along object boundaries. Further, the application of a new optimal machine learning algorithm capable of classifying strong non-linear data such as Random Kitchen Sink (RKS), shows improved classification performance...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227003/automated-segmentation-and-classification-of-cell-nuclei-in-immunohistochemical-breast-cancer-images-with-estrogen-receptor-marker
#14
Julio Oscanoa, Franco Doimi, Richard Dyer, Jhahaira Araujo, Joseph Pinto, Benjamin Castaneda, Julio Oscanoa, Franco Doimi, Richard Dyer, Jhahaira Araujo, Joseph Pinto, Benjamin Castaneda, Jhahaira Araujo, Franco Doimi, Julio Oscanoa, Richard Dyer, Benjamin Castaneda, Joseph Pinto
Breast cancer is the most common malignant tumor in women worldwide. In recent years, there has been an increasing use of immunohistochemistry (the process of detecting the expression of certain proteins in cytological images) to obtain useful information for diagnosis. This paper presents an efficient algorithm that automatically detects breast cancer cell nuclei and divides them into two groups: those that express the ER marker and those that do not. First, the areas that belong to the carcinoma are automatically identified...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226773/biclustering-strategies-for-genetic-marker-selection-in-gynecologic-tumor-cell-lines
#15
A Alevyzaki, S Sfakianakis, E S Bei, E Obermayr, R Zeillinger, D Fotiadis, M Zervakis, A Alevyzaki, S Sfakianakis, E S Bei, E Obermayr, R Zeillinger, D Fotiadis, M Zervakis, R Zeillinger, D Fotiadis, E S Bei, S Sfakianakis, M Zervakis, A Alevyzaki, E Obermayr
Over the past few decades great interest has been focused on cell lines derived from tumors, because of their usability as models to understand the biology of cancer. At the same time, advanced technologies such as DNA-microarrays have been broadly used to study the expression level of thousands of genes in primary tumors or cancer cell lines in a single experiment. Results from microarray analysis approaches have provided valuable insights into the underlying biology and proven useful for tumor classification, prognostication and prediction...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226771/multimodal-characterization-of-radiologically-detectable-lung-lesions
#16
Atasi Sarkar, A Sadhu, S Basu Thakur, S Sengupta, A Mukherjee, Jyotirmoy Chatterjee, Atasi Sarkar, A Sadhu, S Basu Thakur, S Sengupta, A Mukherjee, Jyotirmoy Chatterjee, S Basu Thakur, A Mukherjee, Atasi Sarkar, S Sengupta, A Sadhu, Jyotirmoy Chatterjee
Diagnosing radiologically detectable lung lesions on the basis of cyto/histopathological staining often suffers from ambiguity, leading to faulty detection of lung diseases, especially cancer. Present study attempted to perform a multimodal characterzation of clinical samples from patients with radiologically detected lung lesions, in order to classify diseases with higher precision. The study included analysing nuclear morphometric and intensity based differences between benign and malignant lung lesions in a quantitative way...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226760/a-new-approach-of-oral-cancer-detection-using-bilateral-texture-features-in-digital-infrared-thermal-images
#17
M Chakraborty, S Mukhopadhyay, A Dasgupta, S Patsa, N Anjum, J G Ray, M Chakraborty, S Mukhopadhyay, A Dasgupta, S Patsa, N Anjum, J G Ray, S Patsa, A Dasgupta, N Anjum, M Chakraborty, S Mukhopadhyay, J G Ray
Oral cancer is one of the most prevalent form of cancer and its severity is aggrandized specially among the socio-economically backward population in developing countries. A major fraction of patient population is unable to avail diagnosis for oral cancer due to scarcity of state-of-the-art infrastructure and experienced oral and maxillofacial pathologist. Contemporary gold standard of oral cancer confirmation relies on biopsy report. But biopsy is invasive and thus patients are usually reluctant to undergo this test...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226755/automatic-detection-of-melanoma-using-broad-extraction-of-features-from-digital-images
#18
M H Jafari, S Samavi, N Karimi, S M R Soroushmehr, K Ward, K Najarian, M H Jafari, S Samavi, N Karimi, S M R Soroushmehr, K Ward, K Najarian, K Ward, M H Jafari, S M R Soroushmehr, S Samavi, K Najarian, N Karimi
Automatic and reliable diagnosis of skin cancer, as a smartphone application, is of great interest. Among different types of skin cancers, melanoma is the most dangerous one which causes most deaths. Meanwhile, melanoma is curable if it were diagnosed in its early stages. In this paper we propose an efficient system for prescreening of pigmented skin lesions for malignancy using general-purpose digital cameras. These images can be captured by a smartphone or a digital camera. This could be beneficial in different applications, such as computer aided diagnosis and telemedicine applications...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226682/extraction-of-medically-interpretable-features-for-classification-of-malignancy-in-breast-thermography
#19
Himanshu Madhu, Siva Teja Kakileti, Krithika Venkataramani, Susmija Jabbireddy, Himanshu Madhu, Siva Teja Kakileti, Krithika Venkataramani, Susmija Jabbireddy, Susmija Jabbireddy, Krithika Venkataramani, Siva Teja Kakileti, Himanshu Madhu
Thermography, with high-resolution cameras, is being re-investigated as a possible breast cancer screening imaging modality, as it does not have the harmful radiation effects of mammography. This paper focuses on automatic extraction of medically interpretable non-vascular thermal features. We design these features to differentiate malignancy from different non-malignancy conditions, including hormone sensitive tissues and certain benign conditions, which have an increased thermal response. These features increase the specificity for breast cancer screening, which had been a long known problem in thermographic screening, while retaining high sensitivity...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226577/semi-advised-learning-model-for-skin-cancer-diagnosis-based-on-histopathalogical-images
#20
Ammara Masood, Adel Al-Jumaily, Ammara Masood, Adel Al-Jumaily, Ammara Masood, Adel Al-Jumaily
Computer aided classification of skin cancer images is an active area of research and different classification methods has been proposed so far. However, the supervised classification models based on insufficient labeled training data can badly influence the diagnosis process. To deal with the problem of limited labeled data availability this paper presents a semi advised learning model for automated recognition of skin cancer using histopathalogical images. Deep belief architecture is constructed using unlabeled data by making efficient use of limited labeled data for fine tuning done the classification model...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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