19 results about "Treatment level" patented technology

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 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 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.

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.

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 application discloses a nuclear medicine clinical and continuing education system and method based on structured teaching resources, relates to the technical field of education, and is used for solving the fact that the mastery of related knowledge and experience of students cannot be accurately evaluated, teaching content cannot be adjusted in real time, and the teaching content is single and lags behind in the existing nuclear medicine clinical and continuing education practice, and finally leads to the current situation that the teaching quality is poor. The application comprises the following steps: constructing a nuclear medicine structured teaching resource system; using a learning effect evaluation standard of data collection and data analysis; and designing a personalized multi-level learning mode. The application can realize flexible and personalized teaching interaction in the nuclear medicine clinical and continuing education, can supervise and evaluate the learning effect, improves the teaching quality, and further improves the business ability of the nuclear medicine discipline and the diagnosis and treatment level.

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

The application discloses a peritoneal dialysis patient data processing method and system based on gamification, which comprises the following steps: S1: inputting initial medical data of a patient, and dividing an initial treatment level corresponding to the patient based on the initial medical data; S2: generating and pushing a personalized intervention task to a patient terminal; at the same time, a family support task associated with the personalized intervention task is generated; S3: updating behavior data of the patient; S4: acquiring updated physiological indexes of the patient; S5: judging whether the patient is unlocked to a next treatment level; according to a preset achievement rule, a corresponding virtual achievement is awarded to the patient; and S6: dynamically adjusting the content of the personalized intervention task subsequently pushed to the patient. The application converts a treatment process into a staged gamification task, and combines real-time physiological data and a multi-role cooperative mechanism, so that the cognitive burden of the patient is reduced, the treatment compliance is improved, individualized dynamic management is realized, and a continuous social support system is constructed.

The invention provides a Parkinson's disease auxiliary diagnosis kit based on an RT-QuIC technology and application of the Parkinson's disease auxiliary diagnosis kit, and belongs to the technical field of detection kits. The kit provided by the invention has remarkable minimally invasive property and high patient compliance, detection can be completed only by collecting trace skin tissues, and risks and pains of lumbar puncture or brain tissue biopsy are avoided. The kit has excellent detection performance, can realize highly sensitive and specific identification of early pathology of Parkinson's disease, has a fast detection process, can complete batch sample analysis in a short time, and powerfully supports clinical rapid diagnosis and screening requirements. Meanwhile, the overall cost is remarkably lower than that of existing methods such as imaging, a convenient, reliable and economical molecular detection means is provided for early discovery, clinical auxiliary diagnosis and treatment effect observation of the Parkinson's disease, and positive significance is achieved for improving the overall diagnosis and treatment level of the neurodegenerative diseases.

The invention discloses a method for evaluating the health diagnosis and treatment level of a long and large bridge. The method comprises the following steps: constructing an index system comprising three evaluation objects, namely a health sensing level, a health diagnosis level and a health treatment level; setting five evaluation dimensions of comprehensiveness, accuracy, timeliness, economy and safety under each evaluation object; configuring a plurality of quantifiable or qualitative evaluation indexes and specific representations under each evaluation dimension; under each representation, a grading scoring rule is formulated, and key components are refined for underlying scoring assignment; respectively determining weights of evaluation objects, evaluation dimensions and evaluation indexes through an expert scoring method; determining the importance weight of the component in the characterization index by re-normalizing the relative weight of the key component in the related standard; and based on the weight, performing layer-by-layer comprehensive scoring on the health diagnosis and treatment level of the bridge component by adopting a hierarchical weighting calculation method, and finally outputting a health diagnosis and treatment level evaluation result of the whole long and large bridge. Quantitative evaluation of the health diagnosis and treatment level of the long and large bridge is achieved, and the method also has a reference effect on evaluation of the health diagnosis and treatment levels of other bridges.

Embodiments of present disclosure provide a method, an electronic device and computer product program for predicting an operation outcome. A method of predicting an operation outcome includes determining first prediction model based on a first set of observed data. The method further includes determining a first probability model based on first set of observed objects subjected to first operation and a second set of observed objects subjected to a second operation different from first operation. The method further includes determining a second prediction model based on first set of observed data and first probability model. The method further includes determining first combination of at least the first, second prediction models, and first probability model for predicting a first final outcome of performing first operation on target object. Embodiments of present disclosure improve accuracy of individual treatment effect estimation and can be expanded to application scenarios with multiple treatment levels.

The application discloses a chronic disease acupuncture conditioning multi-modal fusion adaptive decision support system, which is based on traditional Chinese medicine theory and modern algorithm, constructs a whole cycle multi-modal data fusion architecture of "preoperative baseline-intraoperative real-time-postoperative interval-treatment iteration", accurately quantifies acupuncture long-term lag effect and independent intervention effect through time series mutual information, causal forest and other algorithms, builds a treatment level adaptive decision engine to realize functions such as syndrome type drift adaptation and acupoint tolerance correction, combines operation quality control closed loop and multidisciplinary collaborative optimization, solves the core pain points of the prior art, improves the accuracy, safety and accessibility of acupuncture conditioning, provides a standardized and digital solution for non-drug intervention of chronic diseases, and is suitable for whole cycle acupuncture conditioning management of various chronic diseases.

According to the remote monitoring system and method for the in-vitro liver perfusion equipment, medical staff can move and operate a tablet personal computer within a certain range in an operating room without constraint of the physical position of an equipment host, a patient and the equipment can be taken into consideration at the same time, it can be guaranteed that the equipment is normally controlled in a small space or in a multi-person operation scene, and the operation efficiency is improved. The flexibility of the working process is improved; through the Internet cloud, remote specialists can observe the whole perfusion process in real time as if they are personally on site, so that instant remote guidance is provided for evaluation of marginal donor liver and processing of complex conditions, and the utilization efficiency and the treatment level of medical resources are improved; the dual network architecture provides communication redundancy to a certain extent. Based on the alarm pushing function of the cloud platform, 7 * 24-hour state monitoring is realized, even if field personnel leave temporarily, key alarms can be known in time through mobile phones, and the safety is greatly improved.

The application relates to the technical field of a biliopancreatic chronic disease remote cooperative management system, and particularly discloses a biliopancreatic chronic disease remote cooperative management system. The system comprises a medical image data acquisition unit, an individualized anatomical model construction unit, a biliopancreatic fluid dynamics simulation engine, a virtual intervention simulation unit, a risk early warning analysis unit and a remote cooperative diagnosis and treatment platform; a digital twin model of a biliopancreatic duct system of a patient is constructed, the biliopancreatic fluid flow state is simulated in combination with computational fluid dynamics, and virtual stent implantation and other intervention effect pre-performance are supported, so that identification of occult obstruction and quantitative evaluation of a treatment scheme are realized; the system also supports multi-territory expert cooperative consultation, dynamic model updating and risk grading early warning. Through the technical scheme, a leap from morphological diagnosis to functional diagnosis is realized, and early lesion detection rate, individualized diagnosis and treatment level and remote cooperation efficiency are improved.