In this paper, a novel method for automated diagnosis of cervical cancer by extracting cytoplasm and nuclei from cervical cytology images is described. The background is removed by preprocessing methods like Edge sharpening and Adaptive Histogram Equalization. Fuzzy thresholding and Active contours are used for extracting the region of interest containing the cytoplasm and nuclei. The nuclei ar...

Cancer is one of the leading health problems, occurring in various organs and tissues body, its incidence increasing worldwide. Lung cancer deadliest types cancer. Due to worldwide prevalence, number cases, deadly consequences, early detection lung cancer, as with all other cancers, greatly increases chances survival. As diseases, diagnosis only possible after appearance symptoms an examination...

Introduction: In order to simplify the information exchange within the medical diagnosis process, a collaborative software agent’s framework is presented. The purpose of the framework is to allow the automated information exchange between different medicine specialists. Methods: This study presented architecture of a hybrid disease diagnosis system. The architecture employed a learning...

Breast Cancer has become the common cause of death among women. Due to long hours invested in manual diagnosis and lesser diagnostic system available emphasize the development of automated diagnosis for early diagnosis of the disease. Our aim is to classify whether the breast cancer is benign or malignant and predict the recurrence and non-recurrence of malignant cases after a certain period. T...

Still there is a passionate debate in medical world about the best screening method for Breast Cancer. Early detection is an effective way to diagnose and manage breast cancer. Mammography is the most widely used screening modality, with solid evidence of benefit for women aged 40 to 74 years. Even then it has also undergone increased scrutiny for False-Positives with additional testing which i...

   The current study designed and simulated graphene nanosensors for detection of GLY120 tumor-associated carbohydrate antigens. Graphene is a two-dimensional nanosheet that offers a high surface-to-volume ratio and high mobility which increases its sensitivity as a graphene sensor over that of other nanoparticles. The current study simulated graphene sensors with and without GLY12...

Cutaneous malignant melanoma is one of the most frequent types of cancer in the world but if a malignant lesion is detected early, it can be cured without complication. Automated skin lesion analysis attempts to accomplish early detection of malignancy using digital dermoscopic images. We address two challenging applications in automated analysis of dermoscopic skin lesion images: lesion segmen...

Tissue biomarker scoring by pathologists is central to defining the appropriate therapy for patients with cancer. Yet, inter-pathologist variability in the interpretation of ambiguous cases can affect diagnostic accuracy. Modern artificial intelligence methods such as deep learning have the potential to supplement pathologist expertise to ensure constant diagnostic accuracy. We developed a comp...

In an effort to contribute to the development of accurate cancer diagnosis based on gene expression data, this study performs a comprehensive evaluation of multicategory Support Vector Machine (MC-SVM) algorithms applied to the majority of cancer-related gene expression microarray datasets currently freely available to the scientific community. Our results show that: (a) MC-SVMs are very effect...