Bladder cancer pathomics intelligent diagnosis method based on machine learning and prognosis model thereof

Abstract

The invention relates to a bladder cancer pathomics intelligent diagnosis method based on machine learning and a prognosis model thereof, and the method is characterized in that the method comprises the following steps: S1, preforming data acquisition; S2, processing a microscopic pathology image; S3, performing bladder cancer pathological image feature extraction; S4, constructing and inspectinga bladder cancer automatic pathological diagnosis model based on machine learning; and S5, constructing and checking a bladder cancer survival prognosis prediction model based on machine learning. Thebladder cancer pathomics intelligent diagnosis method has the advantages that the bladder cancer pathomics intelligent diagnosis method is constructed based on pathological section microscopic imagemachine learning, effective automatic pathological diagnosis can be achieved, pathological diagnosis is expected to be further promoted to be developed to the efficient and accurate field, and the current situation that domestic pathology physicians are in shortage is relieved; the postoperative survival condition of the bladder cancer patient can be efficiently and accurately predicted, and important guidance opinions are provided for clinical decisions of clinicians.

Description

technical field [0001] The invention relates to the technical field of medical artificial intelligence, in particular, to a pathological intelligent diagnosis method of bladder cancer based on machine learning and a prognosis model thereof. Background technique [0002] Bladder cancer is the most common malignant tumor of the urinary system, and its incidence ranks fourth among male malignant tumors. According to the degree of histopathological differentiation, bladder cancer can be divided into invasive urothelial carcinoma and non-invasive urothelial carcinoma. The latter also includes urothelial dysplasia and urothelial hyperplasia of uncertain malignant potential. [0003] At present, the clinical diagnosis of bladder cancer mainly relies on histopathology, which needs to be diagnosed and differentially diagnosed by a professional and experienced pathologist through the naked eye and the use of a medical microscope. However, some histopathological types of bladder cance...

AI Technical Summary

Problems solved by technology

But about an artificial intelligence pathological diagnosis of bladder cancer patients, and accurately predict the survival and prognosis of bladder cancer patients, promote the research progress of bladder cancer diagnosis and treatment in the field of precision medicine, reduce the workload of pathologists, and provide clinicians with treatment A machine learning-based intelligent diagnosis method of bladder cancer pathology and its prognostic model that provide strong guidance for the decision-making of the plan have not been reported so far

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