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Deep learning-based liquid dung and excrement coverage area Boston scoring model

A deep learning and coverage technology, applied in the field of deep learning and intelligent medical care, can solve problems such as limited prospective research and time-consuming, and achieve high reliability and social value

Pending Publication Date: 2020-10-30
TIANJIN YUJIN ARTIFICIAL INTELLIGENCE MEDICAL TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] At present, the scoring of the BBPS scale is mainly performed by the colonoscopist during the inspection and withdrawal process. The pictures of the three areas of the intestinal tract are intercepted by the colonoscopy equipment and scored according to the evaluation criteria. This is somewhat subjective, and its application is mostly limited to prospective Research does require a certain amount of time and manpower

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  • Deep learning-based liquid dung and excrement coverage area Boston scoring model
  • Deep learning-based liquid dung and excrement coverage area Boston scoring model

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Embodiment Construction

[0020] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0021] It should be noted that the "connection" mentioned in this application and the words used to express "connection", such as "connected", "connected", etc., include not only a direct connection between a certain component and another component, but also a certain One part is connected to another part through other parts.

[0022] It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should also be u...

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Abstract

The invention discloses a deep learning-based liquid dung and excrement coverage area Boston scoring model. The establishment of the Boston scoring model comprises the following steps: a, data acquisition and preprocessing; b, data annotation; c, model training; d, model testing; e, module scoring. The intestinal tract preparation condition of an enteroscope can be effectively and automatically judged, a Boston scale is provided for storing patient examination information and providing reference for doctors, the problems that subjective consciousness is brought in by judgment of the doctors, and time and labor are consumed are solved, and higher reliability and social value are achieved.

Description

technical field [0001] The invention relates to the fields of deep learning and intelligent medical treatment, in particular to a Boston scoring model based on deep learning of the coverage area of ​​feces and feces. Background technique [0002] Colonoscopy has become a standard tool for colorectal cancer screening and prevention. Through colonoscopy, doctors can detect and remove polyps in time to prevent the occurrence of polyp cancer. With the advancement of science and technology, the ability of colonoscopy to detect polyps, especially tiny polyps, has been continuously improved. In order to quantitatively evaluate the ability of digestive endoscopy centers and colonoscopists to detect adenomatous polyps using colonoscopy, the American Society of Digestive Endoscopy clearly stated in the 2006 colon cancer screening and surveillance guidelines that the adenoma detection rate (adenoma detection rate, ADR) as the core standard of colonoscopy quality control. [0003] Th...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/30G16H50/20A61B5/00A61B5/107
CPCG16H50/30G16H50/20A61B5/4255A61B5/1076A61B5/1079
Inventor 王玉峰
Owner TIANJIN YUJIN ARTIFICIAL INTELLIGENCE MEDICAL TECH CO LTD