507 results about "Diagnosis laboratory" patented technology

The invention discloses a multi-agent large-model disease diagnosis knowledge reasoning system based on data dual drive, and relates to the technical field of artificial intelligence assisted medical diagnosis. The system collects patient symptom follow-up records, laboratory test results, observation diagnosis probabilities and expert diagnosis recommendation results in a multi-source manner; time sequence evolution characteristics are extracted, a time sequence diagnosis sensitivity coefficient is calculated, and early recognition of disease risks is achieved; in combination with anti-fact simulation and statistical reasoning, a causal consistency coefficient is obtained and is used for verifying causal reasonability of observation diagnosis and contrast results; based on agent group consensus analysis, calculating a game consistency coefficient for judging the credibility of a diagnosis conclusion; positioning and multi-level verification are carried out on abnormal reasoning steps and knowledge fragments, so that the reliability and safety of a result are guaranteed; continuous optimization of the diagnosis model is realized through a log analysis and knowledge backflow mechanism; according to the invention, the accuracy, interpretability and safety of disease diagnosis can be obviously improved.

The invention relates to a renal transplantation post-operation rejection risk monitoring and early warning method and a renal transplantation post-operation rejection risk monitoring and early warning system. The method comprises the steps of collecting recipient nursing monitoring data, laboratory indexes and transplanted kidney ultrasonic blood flow parameters in a follow-up visit period, performing timestamp alignment, deletion processing and standardization on multi-source data, extracting features to construct a time sequence feature sequence, inputting the time sequence feature sequence into a pre-training risk prediction model, outputting the rejection reaction occurrence probability of the next period, and forming a risk trend. Calculating a nursing sensitive index contribution weight based on the model contribution information, and screening a target nursing monitoring index; and establishing an individualized baseline model to obtain a baseline value and an allowable fluctuation interval, extracting characteristics such as deviation amplitude, direction, rate, fluctuation and continuous deviation duration and the like, and performing individualized calibration on the occurrence probability to obtain a calibration risk score. When the threshold value is not reached and the trend is not triggered, generating a nursing monitoring suggestion of the next period; and pushing early warning and generating grading intervention suggestions when a threshold value is reached or a trend is triggered.

The invention discloses a measurement laboratory anomaly detection and diagnosis method, system and device based on deep learning and a medium, and relates to the technical field of anomaly detection and diagnos.The method comprises the steps that multi-source real-time data are collected and preprocessed; performing alignment processing based on sampling inconsistency among the data sources, and constructing unified data representation; generating a corresponding prediction result by using the prediction model; calculating a comprehensive abnormal score based on the aligned data and the prediction result; comparing the comprehensive abnormal score with a threshold value, and judging whether a comprehensive abnormal state exists or not; if the judgment result is abnormal, performing abnormal cause decoupling processing and causal inference to obtain a candidate root cause set; and inputting the candidate root cause set into a deep learning causal inference model to obtain an anomaly diagnosis result. A physical perception residual scoring mechanism is introduced, a comprehensive anomaly score is combined on the basis of anomaly detection, a weighted calculation method is adopted, and the contribution degree of each data source to an abnormal state can be accurately evaluated.

The invention relates to a laboratory safety detection method and device, equipment and a medium. The method comprises the steps that a networking retrieval module is adopted to select a tool for large-scale data retrieval; guiding an intelligent agent RAG module to screen and verify information by adopting a thinking chain technology; in the generation stage, a contrast decoding method is used, the confidence difference between the reference lexical elements and the illusion lexical elements is calculated, and confidence reweighting is conducted on the reference lexical elements and the illusion lexical elements so as to strengthen real safety information and inhibit model illusion content. And inputting the laboratory scene image, the user input text instruction, the structured comprehensive query instruction and the effective information of all rounds into a multi-mode large language model reinforced by a thinking chain technology to generate a laboratory safety detection report, and proactively providing an optimization suggestion of the laboratory safety layout based on the laboratory safety detection report. According to the invention, the reasoning capability of the model in a complex security scene is enhanced, and the accuracy and reliability of a detection result are improved.

Methods and systems are provided for optimizing the digital scanning of pathology slides in a transportable lab. A computing device-implemented method is described for receiving a plurality of pathology slides in the transportable lab, sorting the plurality of pathology slides based upon pathology slide condition to determine which of a plurality of scanners to utilize, and scanning at least one of the plurality of pathology slides utilizing Whole Slide Imaging or Whole Slide Imaging with Robotic Z-Stacking to generate a digital pathology slide. Transportable systems for scanning pathology slides, as described herein, include a triage stage for analyzing each of the pathology slides for digital scanning, a plurality of first slide imaging apparatuses for Whole Slide Imaging, and a plurality of second slide imaging apparatuses for Whole Slide Imaging with Robotic Z-Stacking.

The invention discloses a cerebral hemorrhage patient tracheotomy risk prediction method and system based on machine learning, and the method comprises the steps: obtaining an initial clinical data set of a target patient, calculating laboratory inspection data according to a predefined rule, and constructing a composite physiological state index to generate a feature vector for prediction; inputting the feature vector for prediction into a risk prediction model pre-trained based on an ensemble learning algorithm to obtain a risk quantitative index; the model interpretation module generates an individualized prediction contribution decomposition result based on an SHAP value calculation framework, and explains the specific influence of each feature on the risk index; and finally comprehensively generating a risk prediction report. According to the method, the feature representation and model prediction capability is enhanced by constructing the composite indexes, and meanwhile, the decision process is transparent and credible by utilizing interpretability analysis, so that clinical risk assessment and decision support are effectively assisted.

The invention discloses a fusion mode health physical examination psychological test system, which belongs to the technical field of psychological test and comprises a physical examination data acquisition module, a psychological test module, a multi-modal data fusion module, a result analysis module and a user interaction module. The physical examination data acquisition module is used for acquiring physiological health data of a user, including physical sign data, laboratory examination data and image examination data; the psychological test module provides a plurality of standardized psychological assessment scales; the multi-modal data fusion module is used for performing feature alignment and information fusion on the physiological health data acquired by the physical examination data acquisition module and the psychological test original data generated by the psychological test module, performing fusion analysis on the physiological health data and the psychological test data through the multi-modal data fusion module, and mining the relevance between the physiological health data and the psychological test data; the problems that traditional physical examination and psychological testing are independent and evaluation is not comprehensive are solved, and more complete health condition cognition is provided for the user.

The invention relates to the technical field of clinical medical treatment, and discloses a disease deterioration risk identification method and system based on depth time sequence clustering enhancement, and the method comprises the steps: 1, obtaining multi-modal clinical sequence data of a patient, including physiological indexes of a time sequence, a laboratory detection result, historical diseases and medication data; 2, performing feature extraction and classification on the patient sequences by adopting a knowledge enhanced sequence clustering method, and grouping the patient sequences according to future outcome distribution of the patient sequences; 3, enabling the model to quickly adapt to a prediction task of a new patient subgroup through a meta-training process; and step 4, based on the trained meta-model, carrying out rapid adaptation on the new patient subtype, and predicting the possibility that the new patient subtype has a deterioration event in a certain time window in the future. The method and the system can effectively learn the disease change mode of the patient under the condition of limited clinical data, improve the prediction accuracy of the new patient subgroup, and are especially suitable for clinical prediction scenes under the condition of small samples.

The present invention relates to a system and a method for measuring and analyzing minimal residual disease (MRD) in pediatric B-cell precursor acute lymphoblastic leukemia (B-ALL) using multiparameter flow cytometry (MPFC). The invention finds application in clinical diagnostics and hematology-oncology for quantifying MRD in B-ALL patients with high sensitivity and specificity, needed for risk stratification, monitoring treatment response, and informing therapeutic decisions. The system comprises interconnected subsystems including an acquisition subsystem with an MPFC instrument, a control and file generation subsystem, and an analytical subsystem. The analytical subsystem incorporates modules for sequential data reduction, automated data cleaning, automated unsupervised data clustering, and interactive cluster analysis. Key advantages include high MRD detection sensitivity (e.g., 10⁻⁵ or 0.001%) and high specificity, without reliance on reference samples or supervised machine learning models, making it applicable in laboratories with different measuring equipment and using different panels of antibodies for identification of leukemic cells.

The present application relates to the technical field of molecular detection, and particularly relates to a specific primer combination for distinguishing Enteromorpha prolifera and related species, application and molecular identification method thereof. The primer combination comprises an upstream primer SEQ1 and a downstream primer SEQ2. The primer sequence of SEQ1 is shown as SEQ ID NO. 01, and the primer sequence of SEQ2 is shown as SEQ ID NO. 02. The primer combination of the present application is designed based on the genomic difference of two kinds of algae, has high specificity and sensitivity, can effectively avoid cross reaction, and ensures the accuracy of the detection result. Meanwhile, combined with the real-time fluorescent quantitative PCR (qPCR) technology, the method can effectively quantify the abundance of Enteromorpha prolifera in environmental samples or laboratory samples, and provides reliable technical support for early warning, tracing analysis and prevention and control strategy of green tide outbreak.

A method for operating and diagnosing faults in a laboratory instrument comprising a plurality of subsystems can include conducting an analysis sequence and a set of diagnostic steps. Such a method can be conducted using diagnostic reagents that contain paramagnetic particles but lack an antibody component. Such a method can also include evaluating a set of instrument subsystems in an order that is opposite to the order in which the subsystems are used during an analysis.

Systems for use with a medical device for controlling an infusion device are provided. In one aspect, a system includes an infusion device that is configurable with operating limit parameters for providing medication to a patient, and a limiting system. The limiting system receives laboratory information associated with a patient, compares current operating parameters of the infusion device with the operating limit parameters in view of the laboratory information for the patient before and during administration of the medication to the patient by the infusion device, determines that administration of the medication by the infusion device should be prevented based on comparing the operating parameters with the operating limit parameters in view of the laboratory information and, responsive to determining that the operation should be prevented, prevents the administration of the medication by the infusion device, and generates a notification indicating that the operating limit parameters require modification.

The utility model relates to the technical field of medical laboratories, in particular to a full-automatic specimen post-processing system which comprises a sample loading module, a blood collection tube post-processing workstation and an output docking port which are matched in sequence, the utility model has the advantages of low cost, low maintenance, high working hour utilization rate and small occupied space, can realize the complex functions of rechecking, auditing, uncovering, quality control and the like, and can be modularized and butted with other functional modules.

The invention relates to a specific antibody aiming at CD228 protein and an antigen binding fragment thereof, which are used for detecting and treating various tumors, such as melanoma, mesothelioma, colorectal cancer and the like. The antibody binding fragment is helpful for diagnosis and treatment of cancers through specific binding with CD228. The invention further comprises antibody drug conjugates (ADCs) which bind a drug to an antibody through a linker, so as to improve the therapeutic effect and reduce the influence on normal cells. Meanwhile, nucleic acids encoding the antibodies or antigen-binding fragments thereof are provided to produce recombinant antibodies or fragments. Besides, the invention also provides a kit which is used for laboratory research, clinical diagnosis and treatment effect monitoring, is beneficial to determining whether tissues or cells express CD228 or not, and provides a new strategy for personalized and precise treatment of cancers.

The application relates to a clinical microbiological examination drug sensitivity test report automatic generation device, and belongs to the technical field of medical instruments. A fixing assembly is arranged in a box body to fix a culture dish at the center of the bottom of a cavity, so that a cavity top measuring assembly can be used to collect a drug sensitivity type label on the culture dish and measure the diameter of a bacteriostatic circle in the culture dish, the artificial measurement efficiency is improved, and the occurrence of false reports is avoided, the accuracy of drug sensitivity results is improved, and a disinfection and sterilization assembly is arranged in the box body, so that sample cross contamination and laboratory pollution are effectively avoided.

This invention discloses an infection early warning model and prediction system for critically ill patients based on multimodal monitoring data, belonging to the field of medical artificial intelligence and clinical decision support technology. The system collects multi-source heterogeneous physiological signals, laboratory test indicators, imaging features, and nursing records from patients. Through a self-designed cross-modal feature fusion algorithm and dynamic weight adjustment mechanism, it constructs a nonlinear infection risk prediction model. Furthermore, time-series segmented coding and adaptive threshold correction methods are introduced during model training to achieve early and accurate infection early warning. Compared with existing technologies, this invention significantly improves the sensitivity and specificity of prediction and maintains stable performance across different departments and diseases.

The present disclosure relates to techniques for preprocessing samples and using preprocessed samples and machine learning models to predict clinical diagnostic tests for a patient from their historical laboratory testing data. Particularly, aspects are directed to obtaining datasets including features and / or historical laboratory test results for subjects, filtering the datasets based on a denoise-balance scheme to obtain filtered datasets, training a machine learning model using the filtered datasets to obtain a trained machine learning model, and providing the trained machine learning model. A candidate machine learning model may be an ensemble of classifiers implemented with a boosting algorithm, and the ensemble is trained by applying base machine learning algorithms on different distributions of the filtered datasets. The ensemble is then combined into a machine learning model having the set of learned model parameters for predicting results for clinical diagnostic tests.

The application belongs to the field of biotechnology detection, and particularly relates to a multiplex PCR detection kit for identifying and distinguishing chicken pullorum salmonella and chicken typhoid salmonella. The kit comprises stn gene detection primers, I137_14445 gene detection primers and ybgL gene detection primers. The kit can quickly, high-throughput and accurately identify and distinguish chicken pullorum salmonella and chicken typhoid salmonella, can replace traditional salmonella serological typing and biochemical identification and other complex procedures, and provides a simple, rapid, reproducible new method for monitoring and laboratory diagnosis of chicken pullorum salmonella and chicken typhoid salmonella.

Based on experimental data, observed i n the Personalized Medicine Laboratory of the requesting institute, which reveal an increase in the inorganic polyphosphate (iPolyp) in fecal samples from subjects affected by colorectal cancer compared to samples from individuals not affected by the same disease, inorganic polyphosphate is suggested as a novel non-invasive biomarker to be detected in fecal samples for the early diagnosis of colorectal cancer, to be associated with other screening methods such as fecal occult blood, in order to provide greater predictivity, i.e., the probability that a subject with a positive diagnostic test is actually affected by colorectal cancer.

The utility model provides a laboratory test tube cleaning machine which solves the problem that manual test tube cleaning efficiency is low, is simple in overall structure and small in occupied space and comprises a workbench, a disc support capable of being driven to rotate is arranged on the workbench, and a plurality of test tube clamping stations are arranged on the outer circumference of the disc support. A liftable cleaning mechanism is arranged at the position, on one side of the disc support, of the workbench, the cleaning mechanism comprises a mechanical arm shell, the front end of the mechanical arm shell is rotationally connected with a vertically-distributed cleaning rod, and a water passing cavity is formed in the cleaning rod; a plurality of water passing holes communicating with the water passing cavity are formed in the side wall of the cleaning rod, and a brush is arranged on the outer wall of the cleaning rod; a cleaning driving assembly for driving the cleaning rod to rotate is arranged in the mechanical arm shell, and a rotating connector is installed at the upper end of the cleaning rod and used for being communicated with an input pipe of cleaning liquid.

Provided are a primer-probe combination for real-time quantitative PCR, a related kit, and a method for using primers to measure the titers of measles, mumps and varicella virus pathogens. The method is applicable to clinical and laboratory detection, is fast and convenient, and has high sensitivity.

The invention relates to the technical field of virus detection, in particular to a fluorescent RT-PCR (Reverse Transcription-Polymerase Chain Reaction) detection probe 1106VP and / or 1106WP and primers 1106VWF and 1106VWR. The invention also discloses a fluorescent RT-PCR detection reagent, a fluorescent RT-PCR detection kit, a fluorescent RT-PCR detection probe, a primer, the fluorescent RT-PCR detection reagent and the application of the fluorescent RT-PCR detection kit in identification of a porcine reproductive and respiratory syndrome NJ-1106R strain and a porcine reproductive and respiratory syndrome non-NJ-1106R strain. The probe and the primer disclosed by the invention are high in specificity and high in sensitivity; the accuracy is high, and the accuracy rate of blind sample detection is 100%; the kit is high in universality, can be used for detecting virus liquid for cell culture in a laboratory, and can also be used for detecting porcine serum and tissue samples in clinical samples. The method is an effective method for identifying the PRRSV NJ-1106R vaccine strain and other PRRSV wild strains.

The application discloses a triple fluorescent quantitative PCR detection kit for simultaneously detecting CHIKV, BFV and RRV, which contains a specific primer probe composition for simultaneously detecting chikungunya virus, Barmah Forest virus and Ross River virus, can simultaneously detect three viruses which are transmitted by insect vectors and cause acute fever with arthralgia symptoms in human beings in one PCR reaction tube, and has excellent specificity and repeatability, and is suitable for routine laboratory diagnosis of suspected samples of alphavirus infection, and provides a rapid and accurate detection method for the epidemiological study of CHIKV, BFV and RRV.

A disposable diagnostic device system is disclosed for rapid detection of biomolecules in biological or environmental samples. The device can include an inlet port, microfluidic channels, and one or more sealed detection chambers containing reagents for nucleic acid or protein analysis. Sample introduction and cap closure can drive fluid into the detection chambers, where amplification reactions such as LAMP, SDA, NASBA, TMA, HDA, RPA, or related methods can occur. Detection may be performed by fluorescence, absorbance, or electrochemical measurement using integrated optical components and sensors. The chambers can be vented through gas-permeable membranes to ensure proper filling and mixing with dried or liquid reagents. The device can incorporate onboard electronics, including heaters, temperature sensors, photodetectors, and circuitry powered by a single battery, with optional NFC communication for wireless data transfer. Results may be displayed on the device or transmitted to a smartphone or electronic health system. The system can provide low-cost, portable, point-of-care testing with turnaround times of less than one hour, eliminating reliance on centralized laboratories. Applications can include veterinary diagnostics, livestock management, environmental monitoring, human diagnostics, and companion animal testing, enabling rapid and accessible screening for pathogens at the point of need.

The invention discloses an amino acid L / D type enantiomer separation and quantitative detection method based on LC-MS, and belongs to the technical field of biological analysis. Aiming at the problems of difficulty in separation of amino acid L / D type enantiomers in human serum, low detection sensitivity, complex analysis process and the like, the method disclosed by the invention is simple in pretreatment, short in instrument collection time, high in chiral enantiomer separation degree, small in matrix effect, high in sensitivity, low in cost and convenient for large-scale clinical sample detection in a laboratory; the method not only can make up the limitation that only the L type is detected at present, but also can provide a key analysis method for early warning of diseases, drug effect and toxicokinetics research and precise medical evaluation.

The invention relates to the technical field of nursing after lung transplantation, in particular to a sequential early warning method for human body composition analysis and non-tubular lung transplantation liquid imbalance, which comprises the following steps of: collecting human body composition analysis, spontaneous respiration, circulation functions and laboratory indexes of a patient after lung transplantation; monitoring frequency and key indexes are set based on 0-6 hours (an ultrahigh-risk period), 6-24 hours (a high-risk period) and 24-72 hours (a recovery period) after operation. A multi-dimensional comprehensive score is calculated through multiple parameters, a liquid state risk grade is determined, early warning of a corresponding grade is started in combination with an early warning condition, a grading intervention strategy is executed accordingly, dynamic monitoring and accurate management of postoperative liquid unbalance are achieved, subjective judgment is converted into a quantitative result through fusion of human body composition analysis and spontaneous respiration parameters, and the postoperative liquid unbalance early warning effect is achieved. And the identification accuracy of excessive liquid or insufficient liquid is obviously improved.

The invention discloses a VTE occurrence risk assessment device. The device comprises a data acquisition module, a data analysis module and an early warning module, the data acquisition module is used for automatically acquiring the age, height and weight of the patient from the hospital information system, acquiring the past medical history, operation duration, family history and symptom signs of the patient from the electronic medical record system and acquiring the laboratory examination result of the patient from the laboratory information system when the evaluation time arrives; the data analysis module automatically evaluates the VTE occurrence risk level of the patient according to the obtained data; and the early warning module automatically generates a corresponding alarm message when the VTE occurrence risk level of the patient is a high risk level, and visually displays the alarm message. According to the method and the system, the assessment result of the VTE generation risk is generated by automatically analyzing related data, so that the time cost of manual acquisition and statistics of nurses is greatly reduced, and the assessment efficiency of the VTE generation risk is improved.