20 results about "Normal population" patented technology

The invention discloses a nervous system function evaluation method and device, computer equipment and a medium, and relates to the technical field of intelligent medical treatment. The specific implementation mode comprises the following steps: acquiring sensor data of a plurality of body parts of daily activities of a user, wherein the sensor data is acquired through a sensor arranged in a home environment; obtaining a plurality of motion function evaluation parameters according to the sensor data; obtaining a nervous system function evaluation result based on the whole-age group normal population data model according to the multiple motion function evaluation parameters; and outputting a neurological function risk index and a risk index of the user according to a nervous system function evaluation result. According to the scheme, the nervous system function is evaluated by obtaining multiple evaluation parameters in daily life, and the accuracy and reliability of the evaluation result and the use flexibility of the evaluation method are improved.

The present invention discloses a genome-wide association analysis algorithm at the gene level based on an EMS population, which relates to the technical field of bioinformatics. The present invention conducts association analysis with genes as the basic unit. The MAF index of SNPs in the EMS population is much lower than that of the normal population, but the MAF value at the gene level is higher than that at the SNP level. Weights are assigned according to the mutation effects of each mutation site, and the total weighted value of all mutations in each gene of a single sample is statistically calculated as the basis for association analysis, greatly reducing the false positive rate of the results and increasing the statistical power of the analysis. At the same time, multiple statistical methods are used for comprehensive evaluation to find the most reliable candidate genes. Compared with GWAS that can only locate a fuzzy interval that may contain multiple genes, the present invention can directly and accurately locate to a single gene, improving the experimental efficiency of functional verification of candidate genes and effectively solving the problems that the prior art cannot afford large-scale analysis of the EMS population and has low analysis power.

The present invention provides a mutant gene, detection and application that causes 3-methylglutaconic aciduria type VII. The mutant gene that causes 3-methylglutaconic aciduria type VII includes a compound heterozygous mutation at the CLPB:NM_030813.6:exon8:c.1016T>G:p.L339R site and the exon1:c.130delG:p.E44Sfs*5 site. The mutant gene can effectively distinguish patients with 3-methylglutaconic aciduria type VII from the normal population. Therefore, the pathogenic gene mutation of the present invention can be used as a biomarker for diagnosing 3-methylglutaconic aciduria type VII. The present invention can be used for screening or diagnosing the genetic diagnosis of 3-methylglutaconic aciduria type VII by detecting whether the subject carries the above-mentioned mutation. The detection kit provided by the present invention can be used to quickly and effectively predict or diagnose 3-methylglutaconic aciduria type VII.

The invention relates to the technical field of thermal infrared image evaluation in image data processing, and discloses a human body temperature sequential objective evaluation method based on an infrared thermal imaging technology, which comprises the following steps: acquiring a thermal infrared image of a normal crowd to obtain an average temperature data set of a plurality of regions of interest of the normal crowd, screening out at least two significant regions of interest with statistical difference from the plurality of regions of interest, arranging and ranking the significant regions of interest according to the average temperature representation value to obtain the temperature sequence representation of the normal population, and comparing the temperature sequence representation of the person to be tested with the temperature sequence representation of the normal population to obtain the temperature sequence representation of the person to be tested. The obtained temperature sequence of the to-be-tested person represents the degree of deviation from the normal crowd. According to the method, the normal sequence of different ROI temperatures can be obtained, the temperature deviation degree of the to-be-tested person relative to the body part of a normal crowd is objectively and quantitatively described through a sequence comparison result, and a doctor is assisted in diagnosing whether the to-be-tested person is abnormal in metabolism or not.

An abnormality detection method for a hot plate for treating a substrate, the method comprising: a measurement step for measuring and storing changes in temperature in the hot plate during substrate treatment; a temperature integration step for integrating the changes in temperature during a plurality of substrate treatments stored in the measurement step; a normal population creation step for creating a normal population that is a normal integration result of a prescribed number of substrates integrated in the temperature integration step; and an abnormality detection step for creating an inspection target population that is an integration result of a predetermined number of inspection target substrates integrated in the temperature integration step, and detecting an abnormality related to the hot plate by comparing the inspection target population with the normal population.

The Endoscopic Adjustable Gastric Barrier represents a groundbreaking innovation in the management of obesity, offering a unique, minimal invasive approach without the complications and limitation of other currently available interventional managements., this revolutionary technique works by dividing the stomach into a smaller, tube-like space for food, without altering the stomach's natural anatomy or functions. This preserves the stomach's function to produce hormones and digestive juices, while effectively reducing food intake hence significant weight loss. What makes this innovation (EAGB) unique is its adjustability and reversibility, and when ideal weight is achieved it can be removed endoscopically. It is secured to the stomach by clips with minimal injury and without risk of necrosis and leak. Additionally, all endoscopic and laparoscopic interventions are possible as normal population.

The invention discloses an abdominal aortic aneurysm serum protein fingerprint detection and analysis method and system based on an LASSO regression algorithm. The method comprises the following steps: by optimizing a serum sample pretreatment process and combining an MALDI-TOFMS (Matrix-Assisted Laser Desorption / Ionization Time of Flight Mass Spectrometry) mass spectrometry technology and high-throughput proteomics data analysis, screening differentially expressed proteins related to occurrence, development and rupture of abdominal aortic aneurysm in serum; and further constructing a risk assessment model based on the key protein combination by using an LASSO machine learning algorithm. The method provided by the invention has the advantages of high sensitivity and good specificity, can effectively distinguish abdominal aortic aneurysm patients from normal people, can accurately predict the rupture risk of abdominal aortic aneurysm, especially early small aneurysm, and provides important tools and bases for clinical early diagnosis, risk stratification and personalized treatment decision.

The embodiment of the invention provides an autism auxiliary diagnosis method. The autism auxiliary diagnosis method comprises the following steps: constructing an individual brain function connection diagram; based on a community detection algorithm of a graph theory, performing functional region division on the individual brain function link graph to generate an individual brain map; taking the surface area percentage of the functional network of the healthy control group in the cerebral cortex as a response variable, taking the individual age as a smooth nonlinear independent variable, introducing an average head movement parameter as a linear covariable, and constructing a normal population development reference model; and comparing the surface area percentage of the functional network of the individual brain map with the normal population development reference model of the same age, and quantifying the deviation degree to realize auxiliary diagnosis of the autism. According to the autism auxiliary diagnosis method provided by the embodiment of the invention, individualized autism auxiliary diagnosis considering individual differences can be realized. The embodiment of the invention further provides an autism auxiliary diagnosis device and electronic equipment.

The present invention provides a method for evaluating body composition and a system for using thereof. The method comprises inputting a body composition index and an individual variable to a body composition prediction model so as to produce a body composition evaluation index. The body composition index, comprising a muscle index, a fat index or a comprehensive index, is measured according to a medical image, and the individual variable corresponds to an individual variable of the medical image. The system is configured to obtain the body composition index and the individual variable, and produces the body composition evaluation index accordingly. By using the method and the system, a quantile and a body age evaluation value of a corresponding individual among a normal population can be obtained, and requires only a medical image or a body composition index produced according thereto, which assists judgement of the individual's health status.

The present invention relates to the field of biomedicine, and more specifically, to a prediction model and method for hypertrophic choroidal disease. The prediction model is constructed by the following steps: S1) Data acquisition: selecting eyes with hypertrophic choroidal disease, eyes with normal hypertrophic choroids, and eyes with normal non-hypertrophic choroids as data collection objects, and collecting the choroidal thickness in the macular region, the thickness of the choroidal medium vascular layer, and the thickness of the choroidal large vascular layer; S2) Data processing: calculating the ratio of the Sattler layer thickness to the Haller layer thickness to obtain the S / H ratio; comparing and analyzing the choroidal thickness and S / H ratio across age groups and groups, and establishing a multivariate regression model; S3) Data output: drawing a receiver operating characteristic (ROC) curve to obtain a prediction model for hypertrophic choroidal disease based on the S / H ratio. This objectively reflects the comparison with healthy eyes in the normal population and those with hypertrophic choroidal disease.

The present invention discloses a genomic biomarker combination for diagnosing keratoconus. Based on the whole-genome sequencing data of keratoconus, the present invention conducts association analysis, screens significant variant sites related to keratoconus, and performs polygenic risk score modeling and susceptibility risk prediction. The results show that the genetic variant risk sites screened by the present invention can effectively distinguish between normal populations and keratoconus populations.

The application provides a method and device for generating a reference brain image, electronic equipment and a storage medium, wherein the method comprises: in response to a received evaluation instruction, obtaining an individual brain image to be evaluated indicated by the evaluation instruction; and inputting the individual brain image into a trained variational autoencoder model to obtain a reference brain image corresponding to the individual brain image output by the variational autoencoder model, the reference brain image being used to indicate brain features in a healthy state of the individual to be evaluated. The AI model is used to reconstruct the brain image of the individual to be evaluated based on brain features of a normal population, so that a more targeted reference brain image is obtained, a personalized normal reference brain image is formed, and the individual health evaluation is better assisted.

The invention discloses a polyadenylation functional site marker related to auxiliary diagnosis of non-small cell lung cancer and application of the polyadenylation functional site marker. The site is rs9606. Large-scale population data and biofunctional experiments prove that the rs9606 site affects the expression of the target gene LYRM4 by affecting the 3 'UTR length of the target gene LYRM4, and finally affects the risk of non-small cell lung cancer. According to the present invention, the rs9606 mutation detection can be performed on the normal population by using the real-time fluorescent quantitative PCR through the specific primer and probe design on the rs9606 site, such that the high risk population of the non-small cell lung cancer can be identified so as to assist the early screening and diagnosis of the non-small cell lung cancer patient. The technical method is reasonable in design, simple and feasible, detection can be carried out only by taking a venous blood sample of a patient, and invasive operation such as tissue biopsy is not needed. The method is accurate and reliable in result, can be popularized in hospitals at all levels, and is greatly helpful for evaluating the risk of non-small cell lung cancer.

The invention discloses an intelligent abnormal psychological behavior screening method for college student groups, and relates to the technical field of psychological screening and artificial intelligence, and the method comprises the following specific steps: inducing a subject to respond through a standardized cognitive task; synchronously acquiring and processing eye movement and electroencephalogram signals; extracting multi-modal physiological features and carrying out fusion calculation to generate a time sequence cognitive coupling feature value; training a time sequence anomaly discrimination model based on the normal group data; and finally, the features of the person to be tested are input into the model, a discrimination coefficient is calculated, a grading screening result is output, and noninvasive, objective and efficient psychological state assessment and early warning are realized. According to the method, a non-invasive screening process suitable for a campus scene is constructed, multi-modal fusion and time sequence dynamic analysis are utilized, the accuracy and objectivity of college student psychological state assessment are improved, graded and personalized screening results and intervention suggestions can be output, and an efficient and quantifiable scientific tool is provided for campus psychological health management.

The invention relates to a method for scoring the distribution deviation degree of tail end feature sequences of a to-be-detected sample and a control sample. According to the method provided by the invention, the deviation of feature distribution of each terminal sequence of cfDNA of a sample to be detected relative to normal people is counted, the proportion of the deviation of each terminal sequence in the sum of the deviation of all the terminal sequences is calculated, and finally, the deviation proportions are accumulated (weighted summation) to obtain the overall deviation, so that the accuracy of the whole deviation is improved. Correcting the frequency of each tail end characteristic sequence in the cfDNA fragment of the sample to be detected by taking the average value of the frequency of each tail end characteristic sequence in the cfDNA fragment or all the cfDNA fragments in the preset length range of the healthy sample as a baseline to obtain a corrected frequency of each tail end characteristic sequence in the cfDNA fragment of the sample to be detected, the interference of different experimental conditions, experimental consumables, different sample collection, different transportation conditions and the like on the deviation of the terminal sequence feature distribution of the cfDNA of the whole to-be-detected sample relative to normal people is eliminated, so that the accuracy of determining the sample source is further improved, and the cancer screening quality is improved.

The present invention relates to a monoclonal antibody against HPV16 E6 oncoprotein, its preparation method and application. The present invention screens and obtains a monoclonal antibody that specifically binds to the HPV16 E6 recombinant antigen. Applying the monoclonal antibody to a biotin-avidin amplified ELISA system can specifically detect the E6 oncoprotein of HPV16, with a sensitivity of 100 pg / mL, no cross-reaction with the oncoproteins of other high-risk HPVs, and showing high specificity and sensitivity in the detection of cervical exfoliated cell samples from normal populations, CIN3 and cervical cancer populations. It can be applied to the early screening of cervical cancer in the future; it is faster and more accurate than traditional exfoliative cytology examinations, and at the same time can avoid the risks of false positives and misdiagnosis caused by the too high sensitivity of nucleic acid detection, and has high application value.

The present application relates to the technical field of nerve electrophysiological examination data processing, in particular to a method and system for nerve conduction examination data interpretation and diagnosis, first performing field extraction, term standardization and other preprocessing on the examination data to obtain a detection item set, performing pre-determination through a preset 15-class peripheral nerve injury disease diagnosis rule base, directly outputting results and determination basis if the diagnosis rule is met, and entering a model interpretation process if not; based on nerve conduction anatomy prior recognition, pairing relationship is identified and contrast features are generated, a direction consistent deviation matrix is constructed in combination with normal population data; multi-dimensional features are fused and a nerve conduction anatomy relationship graph is constructed, a relationship perception heterogeneous graph attention network coding is used by introducing edge type embedding, global features are extracted through contrast perception attention pooling enhanced by pairing difference to realize disease classification. The present application can improve interpretation efficiency and accuracy, reduce subjective errors, and provide objective auxiliary diagnosis support for neuromuscular diseases.

The invention discloses a divalent mercury hypersensitive whole-cell sensor based on a pigment signal and application of the divalent mercury hypersensitive whole-cell sensor in environmental sample detection. The invention provides a recombinant bacterium which is obtained by introducing a DNA fragment A and a DNA fragment B into a recipient bacterium, the DNA fragment A contains a Pmer gene, a merR gene and a vioABCE gene cluster; the Pmer is a bivalent mercury ion responsive bidirectional promoter, the merR gene expression is started in one direction, and the vioABCE gene cluster expression is started in the other direction; the DNA fragment B contains a constitutive promoter and a merC gene which is started and expressed by the constitutive promoter. The divalent mercury hypersensitive sensor constructed by the invention further reduces the sensing colorimetric detection limit and the naked eye direct reading judgment limit, and can be used for monitoring the mercury exposure of low-level normal people.

The invention relates to the technical field of intermediate frequency therapeutic apparatuses, and provides a wireless remote control intermediate frequency therapeutic apparatus control method and system, and the method comprises the following steps: obtaining an actually measured electromyographic signal of a target object, and obtaining a first root mean square value according to the actually measured electromyographic signal; normal crowd electromyographic signals are obtained, and a second root mean square value is obtained according to the normal crowd electromyographic signals; acquiring an actually measured median frequency of the target object and a normal crowd median frequency; acquiring a muscle fatigue degree value of the target object according to the first root mean square value, the second root mean square value, the actually measured median frequency and the normal crowd median frequency; and according to the muscle fatigue degree value and a preset basic frequency value, dynamically adjusting an output pulse frequency value of the intermediate frequency therapeutic apparatus. The muscle fatigue degree value of the target object is obtained, the output pulse frequency value is dynamically adjusted according to the muscle fatigue degree value of the target object and the preset basic frequency value, and the intelligent degree can be effectively improved.

The application discloses a kind of abdominal aortic aneurysm serum protein fingerprint detection analysis method and system based on LASSO regression algorithm.The method is by optimizing serum sample pretreatment process, in combination with MALDI-TOFMS mass spectrometry technology and high-throughput proteomics data analysis, screening the differential expression protein in serum related to abdominal aortic aneurysm occurrence, development and rupture;Further utilize LASSO machine learning algorithm to construct risk assessment model based on key protein combination.The method of the application has the advantages of high sensitivity, good specificity, can effectively distinguish abdominal aortic aneurysm patients and normal population, and can accurately predict the rupture risk of abdominal aortic aneurysm, especially early small aneurysm, provide important tool and basis for clinical early diagnosis, risk stratification and personalized treatment decision.