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Kidney clear cell carcinoma molecular feature prediction and prognosis technology based on pathological pictures

A technology of renal clear cell carcinoma and molecular features, which is applied in the fields of cancer molecular feature prediction, molecular feature prediction of renal clear cell carcinoma and prognosis judgment, which can solve the problems of long waiting time and a lot of money.

Inactive Publication Date: 2021-03-12
曾皓
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  • Claims
  • Application Information

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Problems solved by technology

But these models all require patient sequencing data, a lot of money and a relatively long waiting time

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  • Kidney clear cell carcinoma molecular feature prediction and prognosis technology based on pathological pictures
  • Kidney clear cell carcinoma molecular feature prediction and prognosis technology based on pathological pictures
  • Kidney clear cell carcinoma molecular feature prediction and prognosis technology based on pathological pictures

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Embodiment Construction

[0031] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0032] see Figure 1-5 , the present invention provides a technical solution for molecular feature prediction and prognosis judgment technology of clear cell renal cell carcinoma based on pathological pictures: a technology for molecular feature prediction and prognosis judgment of clear cell renal cell carcinoma based on pathological pictures, molecular features of clear cell renal cell carcinoma Prediction and prognosis judgment techniques include the follow...

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Abstract

The invention discloses a renal clear cell carcinoma molecular feature prediction and prognosis technology based on a pathological picture. The renal clear cell carcinoma molecular feature predictionand prognosis technology comprises the following steps: 1, carrying out feature extraction of the pathological picture; 2, predicting the molecular characteristics of the patient through the pathological picture; 3, integrating a single pathological picture and a pathological picture into multiple omics to predict the lifetime of the patient. According to the method, pathological pictures of patients can be quantified quickly and economically, important mutation states, molecular subtype affiliation and survival time of the patients can be predicted, and the survival time of the patients withexisting gene, transcription or proteomics data can be judged quickly, economically and more accurately.

Description

technical field [0001] The invention relates to a prediction of molecular characteristics of cancer, in particular to a technology for prediction of molecular characteristics and prognosis of renal clear cell carcinoma based on pathological pictures, and belongs to the technical field of cell processing. Background technique [0002] With the development of precision oncology, histopathological images have become the gold standard for tumor diagnosis, grading and staging. At the same time, omics profiling, including genomics, transcriptomics, and proteomics, is becoming a routine method for identifying tumor characteristics and for survival prediction, but the quantitative research on pathological images and its huge potential application value It has not been fully developed, and in renal clear cell carcinoma, the technology in this area is blank. [0003] In the prior art, the analysis of pathological pictures can only be perceived intuitively by the naked eye, and while ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H70/60G16H30/00G16B20/50G16B5/00
CPCG16H30/00G16H70/60G16B5/00G16B20/50
Inventor 曾皓陈琳燕黄也茜李卉廖启蒙
Owner 曾皓
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