Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Artificial insemination success rate influence factor calculating method based on logistic regression and system thereof

A technique of logistic regression and influencing factors, applied in the field of machine learning, can solve problems such as the inability of the model to accurately describe the real scene, and achieve good interpretability, reasonable assumptions, and reduced impact

Inactive Publication Date: 2019-06-25
重庆善功科技有限公司
View PDF5 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the clinical characteristics of the patients are highly correlated, and the multicollinearity of the characteristics is manifested in the linear model, which makes the model unable to accurately describe the real scene.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Artificial insemination success rate influence factor calculating method based on logistic regression and system thereof
  • Artificial insemination success rate influence factor calculating method based on logistic regression and system thereof
  • Artificial insemination success rate influence factor calculating method based on logistic regression and system thereof

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0020] The specific embodiments of the present invention will be described below to further illustrate the starting point and corresponding technical solutions of the present invention.

[0021] figure 1 It is a flow chart of a method for calculating influencing factors based on sparse logistic regression provided by an embodiment of the present invention. The method includes four steps:

[0022] Step 1, collect the structured information of the case, extract the pregnancy information and its related characteristics.

[0023] Preferably, the structured information of the case is collected, and pregnancy information and related features are extracted, including:

[0024] Analyze electronic medical records, design information extraction rules, extract structured information, and convert electronic medical record information into a record in structured text;

[0025] Extract pregnancy information as well as feature information from a text file.

[0026] Preferably, pdfplumber...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention provides an intrauterine insemination success rate influence factor calculating method for a polycystic ovarian syndrome patient based on logistic regression and a system thereof. The method comprises the steps of collecting structured information of a case, extracting pregnant information and a related characteristic; converting the related characteristic so that the characteristiccan be accepted by a user and an algorithm; training a logistic regression model by means of an intersected verifying manner; outputting a model parameter which corresponds with each kind on the condition of an optimal super-parameter, performing highest and lowest normalization on all model parameters, and restraining the parameter to an interval of [0,1] as an influence degree output. Compared with traditional chi-square testing methods, the method according to the invention has advantages of realizing more reasonable hypothesis, reducing influence caused by multiple colinearity of the variable, and realizing good interpretability.

Description

technical field [0001] The invention relates to the field of machine learning, in particular to a method and system for calculating factors affecting the success rate of intrauterine artificial insemination with husband sperm in patients with polycystic ovary syndrome based on sparse logistic regression. Background technique [0002] Assisted reproduction has developed rapidly in modern medicine. Assisted reproduction aims to help infertile couples conceive through artificial manipulation of sperm, egg cells, and embryos. The technique includes artificial insemination and in vitro fertilization-embryo transfer. Intrauterine artificial insemination with husband's sperm refers to a kind of assisted pregnancy technology that collects the husband's semen and injects it into the woman's uterus directly or after treatment. It is widely used in infertility because of its practicality, non-invasiveness and low cost. During treatment. Medical researchers have analyzed the factors ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G16H10/60G16H50/70
Inventor 张玉枫曾品鸿张海轮陈浩雷大江李智星
Owner 重庆善功科技有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com