13 results about "Underlying disease" patented technology

The invention discloses a chronic disease risk prediction method and system fusing a knowledge graph and a large language model, and the method comprises the following steps: obtaining a natural language problem related to a chronic disease, and carrying out the semantic analysis; according to the analysis content, hypothetical questions and answers related to chronic diseases are generated through a large language model, and key entities are extracted; mapping the key entities to corresponding nodes in a medical knowledge graph, exploring a semantic path and a causal relationship between the key entities, and constructing an inference chain pointing to potential disease risks from acquired information; introducing a fragment granularity sensing mechanism, performing fine granularity analysis on each fragment in the reasoning chain, and rearranging and optimizing a link sequence; and based on the optimized inference chain, converting the question and answer result into a structured diagnosis result for visual display. According to the method, the whole process from question asking to answer generation of the patient is optimized, the efficiency and accuracy of chronic disease risk prediction are effectively improved, and meanwhile, personalized health management service is provided for the patient.

The invention relates to the technical field of operation time prediction, in particular to an operation time real-time prediction model based on preoperative and intraoperative information and an artificial neural network, which comprises the following steps: a data acquisition module, construction of an artificial neural network model, a data preprocessing module and real-time deployment. The data acquisition module comprises the following steps of collecting a large amount of performed operation data in advance, including preoperative information, intraoperative information and actual operation time, classifying operation types and difficulty levels, classifying physical states of operation doctors, and performing preoperative acquisition; data of age, gender, weight, health condition, basic disease and previous operation records of a patient are subjected to collection model selection, a neural network is fed forward, and a simple multi-layer sensor is adopted; according to the scheme, the preoperative physical condition of the patient is compared with the previous operation record, the experience of an operation doctor is collected, and the sudden unexpected condition in the operation is predicted, so that the operation time is predicted and evaluated.

The utility model relates to a three-dimensional towed observation system structure for detecting underlying diseases of a railway crossing, which comprises an acquisition device, a traction device, an acquisition host and a vibration excitation device, the acquisition device comprises a plurality of sensors arranged in an array mode, the sensors in the same row are connected one by one, and the traction device is connected with the acquisition host. The traction device is connected with the acquisition device so as to drag the sensors, the acquisition host is connected with the sensors so as to receive measurement data acquired by the sensors, and the excitation device is arranged on one side of the acquisition device and is used for generating vibration data acquired by the acquisition device. The device has the advantages that a three-dimensional result can be formed through one-time excitation in an array type arrangement mode, meanwhile, a pull-type operation mode is adopted, the detection efficiency can be greatly improved, the detection precision can be improved by updating an existing two-dimensional data processing mode into a three-dimensional processing mode, and the interpretation accuracy of crossing underlying diseases can be greatly improved.

The invention relates to the technical field of intelligent hospital guide, in particular to an intelligent hospital guide system based on cloud computing, which comprises a data acquisition port, a data matching port and a disease tracing port, and is characterized in that the data acquisition port is used for acquiring symptom description, medical history, basic physiological indexes, age, gender and patient behavior logs of a patient in real time through multi-source input; the data matching port is used for comparing patient symptoms with a disease database, calculating a symptom matching degree and screening potential diseases; and the disease tracing port is used for locating the most probable disease or department and generating a hospital guide suggestion.

The invention discloses a common animal disease early warning method and system based on breeding environment detection data, and relates to the technical field of animal disease early warning, and the method comprises the steps: interacting a target breeding environment, and obtaining the breeding environment detection data and neighborhood environment data; determining breeding object information of the target breeding environment, calling a pre-constructed disease classifier to perform qualitative classification analysis, and outputting a result as a potential disease set; according to the historical disease data, determining a risk accumulation rate set of M environmental indexes in the breeding environment detection data for a potential disease set; according to the neighborhood environment data and the breeding environment detection data, generating predicted environment sequence data of the target breeding environment, and performing risk accumulation calculation on the potential disease set to obtain an accumulated disease risk of each potential disease; and generating an animal disease early warning report based on the plurality of accumulated disease risks, and executing an early warning response. The technical problem of inaccurate animal disease early warning in the prior art is solved.

The invention relates to the technical field of brain disease diagnosis and treatment decision reasoning, in particular to a diagnosis and treatment decision reasoning method fusing LLM and a knowledge graph, which comprises the following steps of: extracting a plurality of standard entities at least comprising symptom entities and case entities in brain disease cases by adopting a language model; taking the symptom entity and the case entity as a plurality of suspected diseases and candidate diseases corresponding to the retrieval knowledge graph; calculating the disease similarity between each suspected disease and each candidate disease; defining candidate diseases of which the disease similarity is greater than or equal to a similarity threshold value, and forming a potential disease set by taking all suspected diseases as potential diseases; setting each potential disease in the potential disease set as a starting node, and constructing a directed correlation sub-graph based on the knowledge graph; and defining a plurality of examination means corresponding to each potential disease in the directed correlation subgraph as evaluation means, and screening the evaluation means with effective identification capability to construct an evaluation means set.

The invention discloses a septicopyemia early warning method, device and system and a storage medium. The septicopyemia early warning method comprises the following steps: acquiring patient observation data of a target patient under continuous time steps; acquiring a hidden state vector of the target patient under the current time step and a corresponding individualized baseline reference interval; generating an anti-fact observation result in each anti-fact disease cause scene; calculating a disease cause attribution vector and an infection specific residual error of the target patient under the current time step; calculating a septicopyemia event window risk value of the target patient in a preset time window; and outputting risk prompt information of the target patient in the current time step. By adopting the technical scheme of the invention, the problem that the existing early warning method is difficult to distinguish the causes of diseases among patients with multiple basic diseases is solved.

An object of the system according to the embodiment is to unitarily analyze a plurality of symptoms of an individual and specify the possibility of a potential disease.SOLUTION: A system includes a symptom input part, a symptom analysis part, and a database collation part. The symptom input unit collects symptoms input by a user. The symptom analysis unit analyzes the symptoms collected by the symptom input unit. The database collation unit collates the symptom analyzed by the symptom analysis unit with the medical database.SELECTED DRAWING: Figure 1

The application discloses a common animal disease early warning method and system based on breeding environment detection data, and relates to the technical field of animal disease early warning. The method comprises the following steps: interacting with a target breeding environment, obtaining breeding environment detection data and neighborhood environment data; determining breeding object information of the target breeding environment, calling a pre-constructed disease classifier for qualitative classification analysis, and outputting a result as a potential disease set; determining a risk accumulation rate set of M environment indexes in the breeding environment detection data for the potential disease set according to historical disease data; generating predicted environment sequence data of the target breeding environment according to the neighborhood environment data and the breeding environment detection data, performing risk accumulation calculation on the potential disease set, and obtaining an accumulated disease risk of each potential disease; generating an animal disease early warning report based on the multiple accumulated disease risks, and performing early warning response. The application solves the technical problem of inaccurate animal disease early warning in the prior art.

The invention discloses a chronic subdural hematoma model suitable for treatment of artery embolism in meninx, and relates to the technical field of medical research, the model is constructed based on a dura mater structure, and the dura mater comprises a periosteum layer, a meninx layer and a boundary cell layer DBC; according to the method, the chronic subdural hematoma model based on the real structure of the dura mater is accurately constructed, DBC layer damage is finely simulated, the whole process from hematoma origin to intima and adventitia formation is restored, high simulation of disease occurrence and development is achieved, a reliable basis is provided for in-depth exploration of pathogenesis, and the method is suitable for large-scale popularization and application. The biodegradable microspheres are used for simulating artery embolism in the meninx, the microspheres accurately target embolism positions, clinical treatment scenes can be effectively simulated, the influence of embolism on hematoma size, morphological change and intimal and adventitious membrane blood supply can be accurately evaluated, and a multi-modal imaging technology and a data analysis model based on a machine learning algorithm are combined to achieve the purpose of accurate and accurate embolism evaluation. The comprehensive and deep research on the model is realized, and the relevant characteristics of potential disease development and treatment response are mined.

This invention discloses a traditional Chinese medicine composition for the prevention, mitigation, or treatment of Alzheimer's disease, comprising 8-12 parts of Cistanche deserticola, 8-12 parts of Polygonatum sibiricum, 8-12 parts of Panax ginseng, 12-18 parts of Astragalus membranaceus, 12-18 parts of Angelica sinensis, 12-18 parts of Ligustrum lucidum, 8-12 parts of Salvia miltiorrhiza, and 8-10 parts of Panax notoginseng, all by weight. The traditional Chinese medicine composition of this invention significantly improves Alzheimer's disease-related symptoms in a mouse model of Alzheimer's disease, including the novel object recognition index, Y-maze spatial cognition index, water maze activity index, number and distribution of Nissl bodies in neurons, and β-amyloid protein deposition. It is expected to effectively prevent, mitigate, or improve different stages of Alzheimer's disease and its related complications and underlying diseases.

Reanalysis of the SIMPLIFY 1 and 2 trials data indicates MMB is effective in JAKi-naïve patients and in second line therapy to RUX, providing benefits of reducing enlarged spleens, improving myelofibrosis-related symptoms, and increasing transfusion independence in patient at risk for thrombocytopenia from the underlying disease and RUX therapy. Accordingly, methods of treating myeloproliferative neoplasms (MPN) such as myelofibrosis are described. The methods can include administering a therapeutically effective amount of momelotinib or a pharmaceutically acceptable salt thereof to a subject identified as having (i) myelofibrosis and (ii) a platelet count of less than 150×109 / L. Also described are methods including administering to a subject with myelofibrosis a therapeutically effective stable dose of momelotinib or a pharmaceutically acceptable salt thereof, for a period of a plurality of weeks, where the subject is assessed as maintaining a platelet count above a predetermined threshold platelet count during the period.

Reanalysis of the SIMPLIFY 1 and 2 trials data indicates MMB is effective in JAKi-naïve patients and in second line therapy to RUX, providing benefits of reducing enlarged spleens, improving myelofibrosis-related symptoms, and increasing transfusion independence in patient at risk for thrombocytopenia from the underlying disease and RUX therapy. Accordingly, methods of treating myeloproliferative neoplasms (MPN) such as myelofibrosis are described. The methods can include administering a therapeutically effective amount of momelotinib or a pharmaceutically acceptable salt thereof to a subject identified as having (i) myelofibrosis and (ii) a platelet count of less than 150×109 / L. Also described are methods including administering to a subject with myelofibrosis a therapeutically effective stable dose of momelotinib or a pharmaceutically acceptable salt thereof, for a period of a plurality of weeks, where the subject is assessed as maintaining a platelet count above a predetermined threshold platelet count during the period.