6 results about "Pregnancy outcomes" patented technology

The present application relates to the technical field of medical data fusion processing, and discloses a method and system for predicting adverse pregnancy outcomes of preeclampsia by fusing placental microenvironment image features and serum biomarkers, wherein the method comprises: obtaining digital whole field image of placental tissue section and serum biomarker detection data at the same period; constructing a multi-modal sample data set; extracting multi-scale structure features of placental microenvironment; constructing serum biomarker discriminant features; dynamically fusing placental image features and serum marker features; constructing a prediction model for adverse pregnancy outcomes of preeclampsia and outputting a prediction probability. Compared with the prior art which only relies on single image information or single serum biomarker for risk assessment, it is difficult to realize stable prediction of the coordinated changes of placental microenvironment abnormalities and biochemical abnormalities. Due to the multi-scale image structure analysis, the model generalization ability for predicting adverse pregnancy outcomes of preeclampsia is improved.

This invention provides a method and system for integrated data correlation analysis based on clinical features and molecular indicators, belonging to the field of medical data processing and intelligent prediction technology. The method includes: preprocessing collected clinical feature data and molecular indicator data to obtain a standardized structured dataset; extracting key clinical feature subsets and key molecular indicator subsets from the standardized structured dataset, and fusing them to generate a unified multidimensional fusion feature vector; dynamically calibrating at least three clinical phenotypic benchmarks in the unified multidimensional fusion feature vector using a clinical feature data spectrum, whereby the clinical phenotypic benchmarks are defined based on age feature spectrum nodes, infertility course trajectory critical scaling, and endometrial thickness quantification cutoff values. This invention can effectively complete the integrated correlation analysis of clinical features and molecular indicators and predict pregnancy outcomes, meeting the needs of precision clinical diagnosis and treatment.

This invention discloses a method and system for predicting pregnancy outcomes in ovulation induction cycles for PCOS patients, belonging to the field of medical artificial intelligence technology. The method includes: acquiring static and dynamic features of PCOS patients; extracting three time-series derived features from the dynamic features: dominant follicle growth rate, multiple follicle synchronous development index, and follicle size uniformity; inputting the static features into a static channel composed of a fully connected neural network, and inputting the time-series derived features into a dynamic channel composed of a gated recurrent unit network; concatenating the outputs of the two channels in a fusion layer and outputting the pregnancy probability through a classification head. This invention, through a dual-channel architecture that fuses baseline clinical parameters and follicle growth dynamic features, achieves a prediction AUC of 0.79, providing effective support for ovulation induction treatment decisions for PCOS patients.

This invention relates to the field of medical data analysis, and more particularly to a method for assessing the risk of pregnancy outcomes in pregnant women based on multifactor feature analysis. The method includes: acquiring individual measured time-series datasets and baseline reference data for physiological expectations; obtaining a gestational age-specific pathological surge penalty factor by weighting the ratio of angiogenic factors to anti-angiogenic factors; obtaining a cross-system pathological cascade time coupling factor by temporally tracing and coupling abnormal deviations in vascular system indicators and blood system indicators; obtaining a fused feature vector by correcting and fusing the initial linear regression slope features; and obtaining the pregnancy outcome risk assessment result by performing machine learning prediction on the fused feature vector. This method solves the problem that existing prediction methods based on linear regression slope extraction and feature splicing cannot effectively identify gestational age-specific early high-risk signals and cross-system short-term pathological cascade signals.

This invention relates to the field of biotechnology and provides a gene-modified mouse model for tracking migratory organisms, its construction method, and its applications. The invention achieves precise labeling of endogenous migratory organisms by fusing the key structural protein TSPAN4 of the migratory organism with the fluorescent tag RFP and the modification tag Avi-tag, and site-specifically integrating it into the H11 site of mice, thus obtaining a TSPAN4-overexpressing transgenic mouse model. By introducing an LSL structure, the fusion gene is kept in a state of expression shutdown, achieving temporal and spatial specific activation only after mating with tissue-specific Cre tool mice. Multidimensional validation has shown that this model can accurately track migratory organisms in placental trophoblast cells, providing a standardized tool for assessing disease progression under physiological and pathological conditions through differences in migratory organism trajectory, inclusion packaging, and assembly, and can be directly applied to mechanistic studies and drug screening for diseases such as adverse pregnancy outcomes.

This invention relates to the use of baicalin in the preparation of drugs for treating and / or alleviating preeclampsia. The drugs are used to inhibit ferroptosis in placental trophoblasts and / or placental tissue, manifested by increasing the expression level of at least one of GPX4, SLC7A11, and FTH1, increasing GSH content and / or GPX activity, and decreasing Fe... 2+ It can reduce MDA, lipid ROS and / or mitochondrial ROS levels, and improve preeclampsia-related hypertension, proteinuria, placental oxidative stress and adverse pregnancy outcomes. This application can be used to prepare preeclampsia treatment and / or alleviation drugs with baicalin monomer as the active ingredient.