35 results about "Cancer classification" patented technology

A system for classifying a patient's cancer as belonging to one or more Cancer Modules of 1 of 15 different cancer types is provided. The Cancer Modules are useful to identify patient populations and individual patients demonstrating specific prognosis, risk of metastasis and / or recurrence, response or lack of response to drugs, and the like.

The present invention provides specific nucleic acid sequences for use in the identification, classification and diagnosis of various sub-types of lung cancers. The present invention permits one to accurately classify lung cancers based on their miR expression profile without further manipulation. Using microRNA microarray data generated from over two hundred formalin-fixed paraffin-embedded (FFPE) resection samples, fine needle aspiration (FNA) samples and fine needle biopsy (FNB) samples of primary lung cancer, microRNA expression profiles were identified that differ significantly for various sub-types of lung cancer.

An automatic classification method for distinguishing between indolent and clinically significant carcinoma using multiparametric MRI (mp-MRI) imaging is provided. By utilizing a convolutional neural network (CNN), which automatically extracts deep features, the hierarchical classification framework avoids deficiencies in current schemes in the art such as the need to provide handcrafted features predefined by a domain expert and the precise delineation of lesion boundaries by a human or computerized algorithm. This hierarchical classification framework is trained using previously acquired mp-MRI data with known cancer classification characteristics and the framework is applied to mp-MRI images of new patients to provide identification and computerized cancer classification results of a suspicious lesion.

The invention discloses a method and system for predicting cancer. The method includes: performing differential analysis on the gene expression spectrum data of cancer patients and normal people to obtain differential genes; The human gene expression profile data is analyzed to obtain the hub gene; and the gene expression profile data of the differential gene is processed by the variational autoencoder algorithm to obtain the dimensionality reduction data; the gene expression profile data of the hub gene and the dimensionality reduction data Together as the classification features of the preset type of cancer classifier, the precise classification of cancer patients and normal people can be realized through the cancer classifier. The method and system for predicting cancer of the present invention use the gene expression profile data of pivot genes obtained by weighted gene co-expression network analysis and the dimensionality reduction data processed by variational autoencoders as the classification features of the cancer classifier, thereby effectively improving the The accuracy of the cancer classifier achieves the goal of efficiently predicting cancer.

To provide a method for selecting a marker gene useful for cancer classification; a method for classifying cancer using the gene; a method for detecting cancer; a kit usable for the classification method or detection method; and a DNA array carrying the gene. According to the present invention, there can be obtained a gene, wherein expression of the above gene is altered independently from genes each of which expression is altered specifically during cell proliferation and expression level of the above gene is specifically altered depending on every type of cancer samples to be tested, whereby the classification or detection of cancer can be carried out conveniently and quickly without giving surgical treatment. Therefore, the present invention is useful for the diagnosis, the treatment, and the like of cancer.

The invention provides methods for classifying a cancer as susceptible to transmembrane prostate androgen induced (TMEPAI)-directed therapies, and methods for treating such cancers. The field of the invention pertains generally to medicine, pathology and oncology. More particularly, it addresses the treatment of breast cancer, such as triple-negative breast cancer, using a transmembrane prostate androgen induced (TMEPAI)-directed therapy.