47 results about "Treatment level" patented technology

The invention relates to the technical field of cardiovascular disease treatment, and discloses a cardiovascular disease medical decision support method based on a large model, and the method comprises the steps: obtaining multi-modal cardiovascular disease medical data, constructing a multi-source heterogeneous data set, carrying out the preprocessing and feature fusion, and constructing a combined representation model based on the pre-training large model and the fusion of traditional and western medicine knowledge. And designing a hierarchical space-time diagram convolutional network to generate a dynamic physiological state code of the patient, and constructing a multi-target optimization decision tree to generate a treatment scheme containing western medicines, traditional Chinese medicine prescriptions and non-drug intervention. A federal learning framework is adopted to cooperatively train a local model, data security is guaranteed, a global model is optimized, and a curative effect attribution module is further arranged to correct decision deviation. According to the method, multi-modal data and traditional Chinese and western medicine knowledge are integrated, personalized treatment scheme generation is achieved, data safety is guaranteed, and the cardiovascular disease diagnosis and treatment level is improved.

The invention relates to a patient diagnosis and treatment method based on a vector database and a medium, and relates to the technical field of intelligent medical treatment, and the method comprises the steps: collecting patient medical data, vectorizing the medical data comprising digital information, text information and image information, carrying out the feature fusion of the vectorized data, and obtaining a first fusion vector; calculating the similarity between the first fusion vector and a second fusion vector corresponding to each historical patient to obtain a preset number of second fusion vectors with the highest similarity; and obtaining an optimal treatment scheme based on a preset number of second fusion vectors with the highest similarity. Compared with the prior art, dependence on the diagnosis and treatment level of doctors can be reduced with the help of previous excellent diagnosis and treatment cases, a better treatment scheme can be quickly obtained, and the diagnosis and treatment level of existing doctors can be quickly improved.

The invention provides an osteoporosis auxiliary diagnosis method fusing CT image features and a semantic knowledge graph, and the method is characterized in that the method comprises the steps: multi-source heterogeneous data collection and standardization processing; constructing a modal exclusive depth coding network; mapping and aligning a unified semantic space; carrying out multi-level cross-modal attention fusion; self-adaptive segmentation and feature enhancement of anatomical perception are carried out; semantic reasoning guided by the knowledge graph; performing multi-task collaborative diagnosis output; and training optimization and interference elimination. Through automatic multi-modal analysis and intelligent diagnosis, the workload of doctors in the imaging department is remarkably relieved, and the diagnosis time of a single example is shortened to be within 3 minutes from the average 15-20 minutes. The standardized diagnosis process of the system improves the diagnosis consistency among different doctors, reduces the diagnosis deviation caused by experience difference, and helps primary hospitals to improve the osteoporosis diagnosis and treatment level.

The invention provides an intelligent diagnosis and treatment method and system for teenager depression based on large model collaboration, and the method comprises the steps: constructing a remote sensing human living microenvironment and growth soft environment data set, carrying out the preprocessing and feature extraction of the data set, carrying out the space-time matching and characterization of the environment and the brain-behavior clinical data of a subject individual, and carrying out the diagnosis and treatment of the teenager depression. Individual intervention queue data and feature representation matched with the environment are collected; establishing a knowledge graph based on a large model based on the acquired multi-dimensional data; and performing intelligent diagnosis and intervention of environment-brain-behavior enhancement based on the established knowledge graph. Based on a knowledge organization system of environment-brain-behavior auxiliary diagnosis, pathogenesis evaluation and individualized intervention, an environment-brain-behavior multi-dimensional knowledge graph oriented to adolescent depression diagnosis is constructed, and based on a large-model collaborative reasoning mechanism enhanced by environment-brain-behavior multi-dimensional knowledge, the adolescent depression diagnosis is more accurate. An intelligent and precise method system is provided for diagnosis and treatment of juvenile depression, and the diagnosis and treatment level is greatly improved.

The invention discloses a medical image diagnosis auxiliary system based on deep learning, and relates to the technical field of medical image processing. According to the method, through integrity verification, exclusive noise suppression and space standardization processing, dynamic changes of focus characteristics are captured through a time sequence attention mechanism, meanwhile, a medical pathology professional knowledge graph is called to achieve accurate matching of the time sequence focus characteristics, an anatomical structure and pathology type nodes, and the risk of missed diagnosis and misdiagnosis is greatly reduced; the confidence coefficient of a diagnosis assistance conclusion is evaluated through a multi-dimensional factor, manual review is automatically prompted for a low-confidence-coefficient result, dual management and control of system assistance and manual check are formed, meanwhile, standardized focus positioning, pathological type candidate and diagnosis basis can be provided for basic-level or inexperienced doctors, and the diagnosis accuracy is improved. Repeated work such as data arrangement can be reduced for experienced doctors, the doctors are assisted to focus on complex case judgment, the diagnosis and treatment level of a medical team is integrally improved, medical risks are effectively reduced, and the diagnosis and treatment quality and efficiency are improved.

The invention belongs to the technical field of power distribution equipment monitoring, and relates to an intelligent power distribution equipment monitoring and fault early warning system and method, and the system comprises an acquisition unit which is used for obtaining an electric parameter, an environment parameter and an operation state quantity of power distribution equipment and forming time synchronization feature data; the topology unit is used for generating a local topology model according to the relation between the cabinet, the loop and the busbar and outputting topology attributes; the evaluation unit is used for generating an operation state evaluation result based on the feature data and the topological attributes and updating an early warning threshold value; the governance unit is used for performing deduplication, suppression and credibility calculation on the alarm to form a disposal level; the interlocking control unit is used for checking and outputting a control action when the disposal level meets an interlocking condition; and the operation and maintenance unit is used for generating a preventive test plan and updating parameters based on a test result. According to the technical scheme of the invention, topological association and threshold update are introduced into monitoring, evaluation, disposal and control links, so that state recognition and control execution are kept consistent.

The invention relates to the technical field of dental diagnosis and treatment systems, and discloses a dental grading diagnosis and treatment automatic electronic medical record generation and sharing system. A medical record data acquisition module of the system integrates diagnosis and treatment data of different levels of medical institutions and historical treatment information of patients to generate a preliminary medical record data set; the grading diagnosis and treatment judgment module analyzes the illness state based on the preliminary data set, divides diagnosis and treatment levels and corresponding medical institution types, and determines referral necessity and priority; the electronic medical record automatic generation module extracts key information and standardized terms, matches medical record formats of corresponding levels, integrates structured data and unstructured clinical notes, and generates a complete electronic medical record document; the data sharing interaction module establishes a cross-mechanism data transmission channel, controls medical record access authority and modifies records, and realizes information sharing; the authority management control module sets access authority levels of different user roles, records operation logs and access traces, and checks abnormal access behaviors.

The invention relates to the technical field of medical informatization, in particular to a neurosurgical disease diagnosis and prognosis prediction system and method based on machine learning, and the system comprises a data collection module, a processing module, a disease diagnosis module, a prognosis prediction module, a model evaluation module and a result output module. The system fuses clinical, image and survival data, and after preprocessing, screening and feature extraction, disease classification and prognosis prediction are performed by using a support vector machine and a random forest algorithm. Diagnosis and prognosis prediction are obtained by comparing algorithm results, and the model evaluation module dynamically adjusts the algorithm weight and optimizes the prediction accuracy. And finally, the system integrates diagnosis, prediction and evaluation results to generate a visual diagnosis report. According to the innovative design, multi-source data fusion, multi-model collaboration and dynamic optimization are achieved, the diagnosis accuracy and prediction reliability are remarkably improved, powerful support is provided for clinical decision making, and the method is expected to play an important role in improving the diagnosis and treatment level, improving patient prognosis and optimizing medical resource allocation.

The invention provides a doctor scheduling method, system and device and a medium. The doctor scheduling method comprises the steps that doctor information corresponding to doctors in a set area is stored in advance; wherein the doctor information comprises basic personal information of doctors, first-aid treatment levels of the doctors and actual treatment scores corresponding to the first-aid treatment levels; acquiring an actual disease diagnosis result of the patient; determining a disease emergency level of the patient based on the actual disease diagnosis result; and based on the disease first-aid level and the doctor information, doctors in the set area are scheduled to form a target medical group for performing first-aid treatment on the patient. According to the method and the device, the doctors in the set area can be flexibly scheduled according to the disease first-aid level of the patient while the medical requirements of the patient are met.

The invention relates to the field of disease risk prediction models, and discloses a thyroid cancer metastasis risk prediction model and a construction method and application thereof. The construction method of the model comprises the following steps: S1, collecting and preprocessing a sample; s2, gene expression quantity detection; s3, data set division and standardization processing; s4, constructing a deep learning model; s5, performing model evaluation; and the biomarker group for detecting the gene expression quantity in the S2 is composed of RPS4Y1, PKHD1L1, CRABP1, KRT18P8, AGPAT4, CPQ, SLC26A7 and RBP4. The prediction model can be used as a clinical auxiliary diagnosis tool and is used for guiding operation range selection, postoperative follow-up visit strategy making and early intervention of high-risk patients, and the precise diagnosis and treatment level of thyroid cancer is improved.

The invention discloses a distribution and micro collaborative low-voltage diagnosis method and system based on digital twinborn and association mining. The method comprises the following steps: constructing a digital twinborn model of a distribution and micro collaborative power distribution network; analyzing low-voltage spatial-temporal distribution characteristics, screening a governance area, simulating the governance area by using a digital twinborn model, selecting a corresponding governance strategy to adjust the digital twinborn model for simulation again after mining a low-voltage cause, and verifying a governance effect of the selected governance strategy based on a simulation result; and for the governance strategy with the governance effect meeting the requirement, calculating a comprehensive score according to the corresponding simulation result, and taking the governance strategy with the highest comprehensive score as a low-voltage governance strategy. According to the method, the distribution micro-grid collaborative digital twin is constructed, diagnosis and treatment of the low-voltage problem are carried out based on the digital twin and association mining, and the voltage treatment level of the distribution micro-grid is improved.

1. Name of the design product: Graphic user interface for operating a therapeutic instrument for electronic devices. 2. Use of the design product: For an electronic device. 3. Design key points of the design product: Lies in the graphic user interface. 4. Picture or photo that best shows the design key points: The front view of Design 2. 5. Other views are conventional designs, and other views are omitted. 6. Design 2 is designated as the basic design. 7. Use of the graphic user interface: This interface is used to control parameters such as the start and stop of the therapeutic instrument, treatment levels, treatment time, etc. The front view of Design 1 is the initial interface. The first interface change state diagram of Design 1 is the interface presented after clicking the start button in the middle of the bottom of the front view of Design 1. This interface is the treatment preparation interface. The second interface change state diagram of Design 1 is the interface presented when the therapeutic instrument device detects that the treatment head touches the skin in the first interface change state diagram of Design 1. The interaction of Design 2 and Design 3 is the same as that of Design 1.

The utility model relates to a comprehensive endoscope lens suitable for examination of ears, noses and throats simultaneously, and belongs to the technical field of medical instruments. Comprising a mirror body stretching-in section located on the front section and a mirror body handheld operation section located on the rear section. The lens body extending section comprises a slender straight pipe, the length of the straight pipe is 10-12 cm, and the outer diameter of the straight pipe is 3.0-3.5 mm; a mirror surface is arranged at one end, far away from an operator, of the straight pipe, and an included angle of 35-50 degrees is formed between the mirror surface and a plane perpendicular to the central axis of the straight pipe. The utility model provides a comprehensive endoscope lens which is simultaneously suitable for ear, nose and throat examination according to the characteristics of human anatomical structures of most Chinese people in combination with years of clinical practical experience of the inventor in the otolaryngology department, and simplifies the examination process of outpatient service of the otolaryngology department. The diagnosis and treatment cost can be reduced, a satisfactory ear-nose-throat examination effect can be obtained, and the diagnosis and treatment level of the ear-nose-throat department is improved.

The invention discloses a tumor patient regional collaborative follow-up visit method and system based on hierarchical diagnosis and treatment, and belongs to the technical field of medical health information processing, and the method comprises the steps: obtaining the original clinical data of a tumor patient, and extracting an encrypted local gradient vector and a mechanism identifier; inputting the encrypted local gradient vector into a federated aggregation server, and outputting a global risk feature vector; according to the global risk feature vector and the real-time regional resource parameters, calling a target grading evaluation model, and outputting a diagnosis and treatment hierarchy identifier; calling a target referral path optimizer according to the diagnosis and treatment level identifier and the real-time medical institution service capability data, and outputting a minimum-cost referral path; based on the minimum-cost referral path and the diagnosis and treatment level identifier, generating a referral scheduling instruction and issuing the referral scheduling instruction; and acquiring execution feedback data after the referral scheduling instruction is executed, inputting the execution feedback data into the federal aggregation server, and updating the encrypted local gradient vector generation parameters and the model weight parameters. The medical resource utilization efficiency is improved.

A method of detecting inflammation in a subject is provided. The method comprises determining a quantity of amyloid present in fibrin(ogen) protein in a blood sample obtained from the subject, and assigning a level of inflammation in the subject based on the quantity of fibrin(ogen) amyloid determined. A method of determining an effect of a therapeutic treatment on a subject by comparing a pre-treatment level of inflammation with a post-treatment level is further provided.

The application discloses a medical quality quantitative evaluation method and system based on a multi-dimensional symbiotic value network. The method obtains inpatient indication evaluation results, medical connotation quality evaluation results, doctor diagnosis and treatment level evaluation results and their converged evaluation results; generates three-party fusion value evaluation results based on patient result value indexes, medical insurance purchase value indexes and doctor professional value indexes; generates cross-dimension collaborative driving indexes and four-column collaborative quality indexes based on the differences between multi-dimensional evaluation results; and introduces patient five-dimensional values to generate five-dimensional symbiotic evaluation results. The application can further convert basic medical evaluation results into three-party value fusion, cross-dimension consistency diagnosis and patient real value symbiotic evaluation results, and improve the quantification degree, state positioning ability and interpretability of inpatient diagnosis and treatment whole-process evaluation.

The present invention relates to the technical field of medical information processing, and discloses a structured data processing system and method for infectious shock diagnosis and treatment image information. The system includes a processor, an image acquisition module, a multimodal data fusion module and other modules. The image acquisition module acquires CT images, ultrasound images and hemodynamic time series data. The multimodal data fusion module processes them to generate multimodal fusion data, which is then generated into dynamic feature vectors by the dynamic feature extraction module, and then a structured diagnosis and treatment record is generated by the structured processing engine. The anomaly detection module monitors the recorded parameters, the diagnosis and treatment decision-making module generates diagnosis and treatment suggestions according to the anomaly signals, the early warning feedback module provides visual warnings, and the performance monitoring module evaluates the system performance. The invention realizes multimodal data fusion processing, generates structured diagnosis and treatment records, provides accurate diagnosis and treatment decision-making support, has real-time monitoring and system optimization functions, and improves the diagnosis and treatment level and efficiency of infectious shock.

The invention discloses a diagnosis and treatment data security sharing and collaborative reasoning system for a severe medical conjunct, and constructs a unified platform which integrates a standardized data interoperation layer, a security federated access control framework and an intelligent core engine for medical conjunct scene perception. Scattered medical institutions in the medical union are connected into a collaborative, efficient and intelligent severe illness treatment network, safe and real-time sharing of cross-institution data is achieved, intelligent agents are enabled to conduct collaborative reasoning, and therefore high-quality medical resources are sunk to each member unit in the medical union in an AI service mode, and the medical resources are saved. Knowledge and experience of top-level critical experts are converted into services which can be called anytime and anywhere, the problem that expert resources of primary hospitals are insufficient is effectively solved, and homogenization of the in-vivo critical diagnosis and treatment level of the medical combination is promoted.

The invention discloses a method for detecting KCNJ8 gene c.263Cgt; according to the technical scheme provided by the invention, the prevention and treatment efficiency of the hereditary arrhythmia is remarkably improved on the clinical diagnosis and treatment level. KCNJ8-A88G mutation detection is completed within 45 minutes through the ARMS-PCR technology, the mutation allele frequency as low as 0.1% can be accurately recognized through the sensitivity of 99.8%, and the diagnosis period is greatly shortened compared with traditional sequencing. On the treatment level, the KATP channel inhibitor is screened, and arrhythmia after myocardial infarction can be effectively prevented. According to the established'genotype-phenotype-treatment response 'correlation model, not only is the prevention and treatment level of diseases such as the J-wave syndrome improved, but also a conversion benchmark from laboratory basic research to clinical application is established.

The invention discloses a new application of the TIMP1 protein in auxiliary diagnosis, prognosis evaluation and targeted therapy of multiple myeloma (multiple myeloma). Aiming at the problems of lack of effective biomarkers, limitation of treatment strategies and insufficient cognition of non-classical functions of TIMP1 in the prior art, the invention provides the multiple myeloma diagnostic reagent, and early diagnosis is realized by detecting the expression level of TIMP1 protein or mRNA (messenger ribonucleic acid). Meanwhile, a prognosis evaluation model based on the TIMP1 expression level is constructed, and a basis is provided for individualized treatment. Furthermore, TIMP1-targeted multiple myeloma treatment strategies are developed, including small molecule inhibitors and neutralizing antibodies, to enhance anti-tumor effects and reverse drug resistance. The invention further provides a medicine screening method and an individualized treatment scheme, and aims at improving the precise treatment level of multiple myeloma.

Treatment system for containers (1) with a treatment carousel (3) having at least a first and a second treatment level (4, 8), wherein the treatment levels (4, 8) each have a plurality of container receptacles arranged one behind the other in which the containers (1) are movable between a loading position (B) and an unloading position (E) along a transport section, wherein the loading positions (B) and the unloading positions (E) of the treatment levels (4, 8) are arranged at angular positions of the treatment carousel (3) and wherein a first transfer device (6a) is provided which is configured to transfer the containers (1) between an unloading position (E) of the first treatment level (4) and a loading position (B) of the second treatment level (8), characterized in that the length of the transport sections is at least between the first and the second treatment level (4,8) to differ from each other.

The invention discloses a method and system for fusing respiratory monitoring and atomization treatment, and relates to the technical field of intelligent rehabilitation. According to the method, firstly, a classified respiratory disease diagnosis model based on machine learning is constructed and trained based on historical respiratory system data of a large sample patient, and text, image and sound diagnosis models are fused to improve the diagnosis accuracy. Meanwhile, a historical data and breathing parameter correlation model is established, and a matching value is analyzed. Real-time breathing parameters are collected through a breathing sensor on the atomizer, and after matching value correction, the illness state is diagnosed in real time through a diagnosis model in combination with multi-source data. And constructing a model library according to the historical diagnosis and treatment data of the patient, generating a personalized treatment scheme, decoding the personalized treatment scheme into atomization treatment data to control an atomizer for treatment, and monitoring the curative effect. And optimizing the diagnosis model according to the treatment effect by using a reinforcement learning algorithm. Precise diagnosis, personalized treatment and dynamic evaluation of respiratory diseases can be achieved through the atomizer, the treatment level of the respiratory diseases is improved, and the health condition of a patient is improved.

Disclosed are methods for preparing a patient-specific vedolizumab dosing regimen for an individual in need thereof, comprising accessing, using a processor, a memory; selecting a first model stored in the memory; forecasting, based on the selected first model, a patient-specific predicted concentration time profile of the vedolizumab, selecting a dosing regimen, based on said forecasting, wherein said dosing regimen achieves a treatment objective, said treatment objective being a therapeutic level of vedolizumab; and outputting said dosing regimen. Further disclosed are methods of treating an individual having an inflammatory bowel disease.

The present application relates to a kind of based on artificial intelligence and multi-agent collaborative hemodialysis multi-source heterogeneous data management method, comprising: collecting hemodialysis related multi-source heterogeneous data, the heterogeneous field in it is standardized mapping, obtain first standard dialysis data;Carry out data anomaly and logic anomaly detection, according to the detection result respectively executes corresponding data processing operation after, obtain second standard dialysis data;Second standard dialysis data is carried out time alignment and longitudinal integration, establishes respectively for treatment level time series, patient level longitudinal dynamic trajectory and cohort level cross-sectional data Multi-level index structure, obtain third standard dialysis data;Third standard dialysis data is based on generation equipment operating parameter derivative feature, cross-modal fusion feature and longitudinal trend feature;Through multi-agent collaborative architecture executes above-mentioned management process.The present application can realize the automatic, standardization, high-quality management of hemodialysis multi-source data.

The present invention discloses a method and system for assessing the risk of noise-induced hearing loss, specifically related to the technical field of hearing loss diagnosis, including: obtaining the auditory characterization data of I sample individuals, where I is an integer greater than zero; the auditory characterization data includes individual genetic data, environmental exposure data, individual physiological data, and behavioral data; inputting the auditory characterization data of I sample individuals into a pre-constructed auditory analysis model to obtain a first screening result, and the first screening result includes Q extreme individuals; based on a comprehensive method of multi-dimensional data, accurate assessment models, and big data analysis, the present invention can not only analyze in detail the causes of current hearing loss, but also predict future risks and provide customized protection suggestions for individuals, thereby improving the efficiency and effectiveness of auditory health management at both the prevention and treatment levels.

The invention relates to the field of biological medicine, discloses application of UCHL1 in preparation of a detection product for predicting the curative effect and prognosis of a hepatocellular carcinoma atelizumab combined with bevacizumab, and further discloses a kit for predicting the curative effect and prognosis of the hepatocellular carcinoma atelizumab combined with bevacizumab. The UCHL1-based kit disclosed by the invention can be used as a curative effect prediction tool for Atezo / Bev immune combined treatment, provides precise treatment guidance for HCC patients, and improves the individualized treatment level.

The invention provides a biomarker for predicting early myocardial infarction and application of the biomarker. The biomarker is obtained by analyzing the super-acute stage (lt; a series of novel biomarkers capable of early predicting the occurrence risk of the myocardial infarction super-acute stage are screened from metabolites with significant difference in plasma samples of patients and normal people, are used for constructing a diagnostic model of the early myocardial infarction super-acute stage, can be used for efficient detection of the myocardial infarction super-acute stage, and can be applied to clinical diagnosis of the myocardial infarction super-acute stage. According to the kit, sensitivity and specificity diagnosis and accurate diagnosis and evaluation of acute myocardial infarction patients and potential high-risk groups in a super-acute stage within 6 hours can be realized, so that the early diagnosis rate of acute myocardial infarction can be improved, implementation of accurate medical strategies can be guided, and the treatment level of acute myocardial infarction can be improved.

The present invention belongs to the field of stroke diagnosis and evaluation, and specifically relates to a marker, a kit and a drug for diagnosing, differentially diagnosing and prognostic evaluation of stroke. The present invention found that the expression of ninjurin1 in stroke patients was significantly higher than that in healthy controls, and the expression level of ninjurin1 was positively correlated with the severity of stroke. Based on this, a marker of stroke is provided, which can be used as a detection target molecule for stroke diagnosis and differential diagnosis reagents, and is applied to the diagnosis, efficacy observation and prognosis evaluation of stroke patients. It can improve the diagnosis and treatment level of stroke and is suitable for clinical promotion and application.

The invention discloses a children respiratory tract infectious disease clinical decision support system and method, and relates to the technical field of health data diagnosis decision, and the method comprises the steps: mining a distributed calculation framework of children respiratory tract infectious diseases; performing multi-source data fusion on the reference data and the distributed computing framework; dynamic monitoring and early warning of a clinical intelligent diagnosis model are established through the internet technology, the health state change of a child patient is tracked, and clinical decision-making of the respiratory tract infectious diseases of the child is completed. According to the method, the comprehensiveness and reliability of data are improved, the health state change of the child patient is tracked in time, early recognition and precise treatment are realized, the data safety and privacy protection are guaranteed, powerful support is provided for clinical decision making, and the diagnosis and treatment level of the child respiratory tract infectious diseases is remarkably improved.

The present invention discloses a medical machine translation method based on reinforcement learning, comprising the steps of constructing a parallel corpus, establishing a machine translation model, pre-training the basic parameters of the machine translation model, constructing a test set to calculate the translation quality score, constructing a reinforcement learning training set, and fine-tuning the optimized parameters of the machine translation model. This invention makes the translation of professional content in the medical vertical field more accurate and convenient, helping medical professionals, research institutes, institutions, and pharmaceutical and medical device companies to quickly understand and learn about the world's most advanced medical information knowledge and medical industry development trends, effectively improving the clinical diagnosis and treatment level and consultation efficiency of medical practitioners.