Here the inventors describe a tumor classifier based on protein expression. Also disclosed is the use of proteomics to construct a highly accurate artificial neural network (ANN)-based classifier for the detection of an individual tumor type, as well as distinguishing between six common tumor types in an unknown primary diagnosis setting. Discriminating sets of proteins are also identified and are used as biomarkers for six carcinomas. A leave-one-out cross validation (LOOCV) method was used to test the ability of the constructed network to predict the single held out sample from each iteration with a maximum predictive accuracy of 87% and an average predictive accuracy of 82% over the range of proteins chosen for its construction
In clinical diagnostics, it is of outmost importance to correctly identify the source of a metastati...
Prostat cancer is a disease which is the most common and which is also the second deadly in men. Whe...
AbstractCancer is a dreadful disease. Millions of people died every year because of this disease. It...
Here the inventors describe a tumor classifier based on protein expression. Also disclosed is the us...
The purpose of this study was to develop a method of classifying cancers to specific diagnosticcateg...
In recent years, the advent of experimental methods top robe gene expression profiles of cancer on a...
Pathological changes in an organ or tissue may be reflected in proteomic patterns in serum. The earl...
Abstract: Tumor is a group of diseases that involve abnormal increases in the number of cells, with ...
In this paper an Artificial Neural Network (ANN) model, for predicting the category of a tumor was d...
Hepatocellular carcinoma (HCC) is a heterogeneous cancer and usually diagnosed at late advanced tumo...
Abstract: Tumor is a group of diseases that involve abnormal increases in the number of cells, with ...
Determination of malignancy in thyroid nodules remains a major diagnostic challenge. Here we report ...
We propose a method for discrimination and classification of ovarian with benign, malignant and norm...
Abstract Many studies have proven the power of gene expression profile in cancer identification, how...
In clinical diagnostics, it is of outmost importance to correctly identify the source of a metastati...
In clinical diagnostics, it is of outmost importance to correctly identify the source of a metastati...
Prostat cancer is a disease which is the most common and which is also the second deadly in men. Whe...
AbstractCancer is a dreadful disease. Millions of people died every year because of this disease. It...
Here the inventors describe a tumor classifier based on protein expression. Also disclosed is the us...
The purpose of this study was to develop a method of classifying cancers to specific diagnosticcateg...
In recent years, the advent of experimental methods top robe gene expression profiles of cancer on a...
Pathological changes in an organ or tissue may be reflected in proteomic patterns in serum. The earl...
Abstract: Tumor is a group of diseases that involve abnormal increases in the number of cells, with ...
In this paper an Artificial Neural Network (ANN) model, for predicting the category of a tumor was d...
Hepatocellular carcinoma (HCC) is a heterogeneous cancer and usually diagnosed at late advanced tumo...
Abstract: Tumor is a group of diseases that involve abnormal increases in the number of cells, with ...
Determination of malignancy in thyroid nodules remains a major diagnostic challenge. Here we report ...
We propose a method for discrimination and classification of ovarian with benign, malignant and norm...
Abstract Many studies have proven the power of gene expression profile in cancer identification, how...
In clinical diagnostics, it is of outmost importance to correctly identify the source of a metastati...
In clinical diagnostics, it is of outmost importance to correctly identify the source of a metastati...
Prostat cancer is a disease which is the most common and which is also the second deadly in men. Whe...
AbstractCancer is a dreadful disease. Millions of people died every year because of this disease. It...