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109 results about "Stromal tumor" patented technology

A stromal tumor is a tumor that arises in the supporting connective tissue of an organ.

Cyclopropane amides and analogs exhibiting Anti-cancer and Anti-proliferative activities

Compounds of the present invention find utility in the treatment of mammalian cancers and especially human cancers including, but not limited to, malignant melanomas, solid tumors, glioblastomas, ovarian cancer, pancreatic cancer, prostate cancer, lung cancers, breast cancers, kidney cancers, hepatic cancers, cervical carcinomas, metastasis of primary tumor sites, myeloproliferative diseases, chronic myelogenous leukemia, leukemias, papillary thyroid carcinoma, non-small cell lung cancer, mesothelioma, hypereosinophilic syndrome, gastrointestinal stromal tumors, colonic cancers, ocular diseases characterized by hyperproliferation leading to blindness including various retinopathies, diabetic retinopathy, rheumatoid arthritis, asthma, chronic obstructive pulmonary disease, mastocytosis, mast cell leukemia, and diseases caused by PDGFR-α kinase, PDGFR-β kinase, c-KIT kinase, cFMS kinase, c-MET kinase, and oncogenic forms, aberrant fusion proteins and polymorphs of any of the foregoing kinases.
Owner:DECIPHERA PHARMA LLC

Deep learning-based intelligent detection method for nuclear division images in gastrointestinal stromal tumor

ActiveCN111798425ARealize the judgment of the degree of dangerAccurate intermediate dataImage enhancementImage analysisStromal tumorNuclear division
The invention discloses a deep learning-based intelligent detection method for nuclear division images in gastrointestinal stromal tumor. The method comprises the following steps: preprocessing an obtained hematoxylin-eosin staining pathological image; taking EfficientDet-D0 as a deep learning detection model, and carrying out training; using U-Net as a deep learning segmentation model, and training the deep learning segmentation model; constructing a deep learning classification model; training the deep learning classification model; detecting the hematoxylin-eosin staining pathological imageof the testee by using the trained deep learning detection model; segmenting the pathological image by using a deep learning segmentation model, and detecting the segmented result; and comparing thenuclear division images detection result based on the deep learning detection model with the nuclear division images detection result based on the deep learning segmentation model to obtain a final classification result. According to the invention, the input hematoxylin-eosin staining image is analyzed, and the number of nuclear division images is detected, so that the judgment on the risk degreeof gastrointestinal stromal tumor is realized.
Owner:TIANJIN UNIV +1

Ultrasonic endoscope, artificial intelligence auxiliary identification method and system, terminal and medium

The invention belongs to the technical field of medical artificial intelligence, and discloses an ultrasonic endoscope, an artificial intelligence auxiliary identification method and system, a terminal and a medium, and the method comprises the steps: obtaining the image data of an ultrasonic endoscope video or a static image in an ultrasonic endoscope monitor in real time through an image collection module, and intercepting an image frame; segmenting and extracting the tumor part image based on the acquired image by adopting artificial image segmentation or utilizing a deep learning segmentation model through an image segmentation module; unifying the sizes of the segmented images through an image conversion module, and carrying out normalization processing to obtain a modularized picture, namely a standardized lesion part image; dividing the modular picture into an interstitial tumor image or a smooth myoma image by using a deep learning classification model through an image classification module; and outputting an image classification result through an output module. According to the method provided by the invention, the image identification accuracy can be effectively improved, and misdiagnosis is reduced.
Owner:THE AFFILIATED HOSPITAL OF QINGDAO UNIV

Construction method of gastrointestinal stromal tumor malignant potential classification model based on support vector machine

The invention belongs to the fields such as oncology, iconography and machine learning, and relates to a construction method of a gastrointestinal stromal tumor malignant potential classification model based on a support vector machine. The construction method according to the invention comprises the steps of data acquisition, namely performing thin-layer CT image acquisition in a belly reinforcing period; extracting and screening a characteristic; obtaining a punishment parameter and a kernel function parameter through cross validation; establishing a classification model through the parameters; and checking model classification performance. The classification model which is constructed according to the method and is based on the support vector machine can accurately classify the gastrointestinal stromal tumor to two kinds, namely a low malignant potential kind and a high malignant potential kind. Furthermore the classification model is based on an existing image resource and does not cause an additional cost of a patient, thereby facilitating clinical popularization.
Owner:NANFANG HOSPITAL OF SOUTHERN MEDICAL UNIV

Application of DKK4 gene and coding protein thereof in preparation of medicament

The invention provides application of a DKK4 gene and a coding protein thereof in preparation of a medicament, in particular application in preparation of a medicament for detecting or treating a gastrointestinal stromal tumor (GIST). The medicament is a detection medicament consisting of a DKK4 antibody serving as an active ingredient and a medicinal carrier or consisting of a DKK4 specific primer serving as an active ingredient and a medicinal carrier. The medicament is a detection kit prepared from the DKK4 antibody or the specific primer thereof serving as the active ingredient and a medicinal carrier. Early diagnosis of the GIST or prognosis of a GIST patient accepting operative treatment is realized by using the detection based on the DKK gene and the product thereof in serum/ tissues; through high-flux chip screening established on the gene level, real-time quantitative polymerase chain reaction (PCR) verification and large clinical sample verification on the protein level, the results are reliable; according to the experimental results, the DKK4 can remarkably distinguish tumor and non-tumor, high-risk tumor and low-risk tumor on both the gene level and the protein level, and the repeatability of the results is high; and the difference of the expression quantity of the DKK4 gene between different groups is huge, and the DKK4 gene has a good clinical application value.
Owner:RENJI HOSPITAL AFFILIATED TO SHANGHAI JIAO TONG UNIV SCHOOL OF MEDICINE
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