Breast cancer is a prevalent disease that affects mostly women, and early diagnosis will expedite the treatment of this ailment. Recently, machine learning (ML) techniques have been employed in biomedical informatics to help fight breast cancer. Extracting information from data support clinical tedious time-consuming task. The use feature extraction has significantly changed whole process diagn...

Lung cancer causes the most deaths worldwide and has one of lowest five-year survival rates all types. It is reported that more than half patients with lung die within year being diagnosed. Because mediastinal lymph node status important factor for treatment prognosis cancer, aim this study to improve predictive value in assessing computed tomography (CT) lymph-node malignancy primary cancer. T...

Breast cancer is the second leading cause of cancer deaths after lung cancer. In order to avoid mortality due to breast cancer, an efficient computer aided diagnosis system for early prediction of breast cancer is needed. In this paper, an efficient computerized system is designed for the classification of Microcalcification Clusters (MC) in digitized mammograms. The proposed system uses Dual T...

Accurate cancer classification is very important to cancer diagnosis and treatment. As molecular information is increasing for the cancer classification, a lot of techniques have been proposed and utilized to classify and predict the cancers from gene expression profiles. In this paper, we propose a method based on speciated evolution for the cancer classification. The optimal combination among...

• Develop an optimal deep learning based colorectal cancer classifier model. Present Adam optimizer with MobileNet-based feature extractor. Employ galactic swarm optimization LSTM model for classification. Validate histopathological images from the Warwick-QU database. In this era of “precision” medicine, image-guided intervention (IGI) enables real-time customized and accurate treatment using ...

Lung cancer is the leading cause of cancer-related death worldwide due to late diagnoses and limited treatment interventions. Recently, comprehensive molecular profiles of lung cancer have been identified. These novel characteristics have enhanced the understanding of the molecular pathology of lung cancer. The identification of driver genetic alterations and potential molecular targets has res...

drug resistance enables cancer cells to break away from cytotoxic effect of anticancer drugs. identification of resistant phenotype is very important because it can lead to effective treatment plan. there is an interest in developing classifying models of resistance phenotype based on the multivariate data. we have investigated a vibrational spectroscopic approach in order to characterize a sen...

background: north of iran is amongst high incidence rate areas of gastric carcinoma where environmental carcinogenic compounds especially agricultural pesticides are massively used. cytochrome p450 2e1 (cyp2e1) enzyme metabolically activates a large number of low molecular mass xenobiotics. the polymorphic nature of cyp2e1 gene control elements is associated with interindividual differences for...

Dukes's classification for colorectal cancer is simple, and correlates well with survival. This study assessed whether the principles of Dukes's classification applied to gastric cancer resulted in the separation of prognostically useful groups. The cumulative survival curves determined by Dukes's, Astler-Coller's (another classification for colorectal cancer), and the Japanese classification f...

Abstract — Classification is one of the major issues in Data Mining Research fields. The classification problems in medical area often classify medical dataset based on the result of medical diagnosis or description of medical treatment by the medical practitioner. This research work discusses the classification process of Gene Expression data for three different cancers which are breast cancer...