9 results about "Disease outcome" patented technology

The application discloses a pig disease diagnosis and treatment teaching training method, device and equipment based on AR, which comprises the following steps: loading a three-dimensional sick pig model corresponding to the current teaching scene through an AR device, and presenting the current symptom performance including visual elements and sound at the corresponding part of the three-dimensional sick pig model; receiving the diagnosis and treatment decision input by a user according to the current symptom performance; analyzing the diagnosis and treatment decision based on a preset pharmacology-pathology response model, updating the symptom state of the three-dimensional sick pig model according to the analysis result, and presenting the updated symptom state in real time as corresponding AR visual effects; when the user confirms the completion of the diagnosis and treatment operation based on the updated symptom state, comprehensively scoring the drug selection accuracy, dosage rationality, processing timeliness and diagnosis and treatment process integrity of the user in the diagnosis and treatment process, and generating a teaching evaluation report. The interactive training scheme can simulate a complete diagnosis and treatment process, support autonomous decision-making and dynamically feedback the disease outcome, and improves the teaching interactivity.

A method is provided for predicting a disease outcome using a machine learning model that generates training data for training the machine learning model useful for implementing a cellular disease model.SOLUTION: A method for predicting a disease outcome using a machine learning model includes implementing an ML-enabled cellular disease model to validate an intervention, identifying a patient population likely to be a responder to the intervention, and developing a therapeutic structure activity relationship screen. To generate a cellular disease model, data from human genetic cohorts, the literature, and generic cellular or tissue-level genomic data are combined to elucidate a set of factors (e.g., genetic, environmental, cellular factors) that cause a particular disease. A series of factors are used to manipulate invitro cells to generate training data for training a machine learning model useful for implementing a cellular disease model.SELECTED DRAWING: FIG. 1B

The invention discloses a health status assessment method and device, electronic equipment and a storage medium, and through the method and the device, traditional physiological index data and neurological function defect symptom data of a user can be collected at the same time by means of mobile terminal equipment, so that the blank of neglecting of digital collection of early symptoms of neurological function defect in an existing method is filled; then the two types of data are analyzed through a multi-dimensional health data fusion analysis model, internal association between the data and cerebrovascular disease outcome and relapse is fully mined, and the problems that only traditional physiological index monitoring is relied on, neglect is given to digital acquisition of early symptoms of neurological impairment, multi-modal data fusion analysis is lacked, and the accuracy of data analysis is poor are solved. The technical effects that early warning signals of the cerebrovascular diseases are accurately captured, the accuracy rate of health state evaluation and early warning is improved, a health management scheme meeting individual requirements is generated, the out-of-hospital rehabilitation monitoring and intervention effect is enhanced, and long-term scientific management of the cerebrovascular diseases is assisted are achieved.

The invention discloses an inflammatory bowel disease accurate diet intervention scheme generation method and system based on multi-modal data integration, and relates to the technical field of diet and health management. The method comprises the following steps: acquiring crowd health data from a plurality of data sets; analyzing and marking the acquired crowd health data; constructing an identification rule and consistency calibration model of the macroscopic phenotype combination features; constructing a biomics alignment data structure reflecting diet and lifestyle-clinical medication-disease outcome association; performing reliability weighting on the macroscopic phenotypic information of the individuals, and endowing each layer of data of different data sets with corresponding weights; constructing a multi-dimensional comprehensive data matrix; establishing a precise diet model; and generating an individualized diet intervention scheme, continuously collecting follow-up visit data, feeding back the follow-up visit data to the model, and dynamically updating model parameters. According to the invention, an accurate diet scheme with high individual suitability can be generated, the dynamic optimization capability is realized, and the diet intervention accuracy and long-term management effect of the patient with the inflammatory bowel disease are improved.

The invention discloses a self-adaptive pre-inquiry and structured hospital guide method based on a multi-modal large model. The method comprises the following steps: in response to a pre-inquiry request which is initiated by a client and contains multi-modal medical data, determining a session time anchor point, and constructing a session context corresponding to the pre-inquiry request based on the session time anchor point; based on the session context, a structured inquiry instruction used for information collection is generated, and the structured inquiry instruction at least comprises a question text and candidate answers corresponding to the question text; receiving user response information which is returned by the client and responds to the structured inquiry instruction, and updating the session context based on the user response information to obtain a complete inquiry context; and based on the complete inquiry context, utilizing a multi-modal large model to infer candidate disease directions so as to generate candidate disease results for hospital guidance. According to the invention, the technical problem of context splitting in the existing hospital guide technology is solved.

This invention discloses a kit, its application, and its method for evaluating the prognostic outcome of liver failure. The invention analyzes the correlation between high-throughput transcriptome sequencing and disease outcome (death, survival), and verifies the results using qPCR. The results show that VSIG4 is specifically highly expressed in patients with poor liver failure outcomes (death) and has a strong, stable, and reliable correlation with the outcome (death, survival). The kit's detection process is simple, reproducible, and can be performed by qualified technicians, making it highly feasible. It provides accurate early warning and prediction results for liver failure outcomes, promptly reflecting the disease status of liver failure patients. This allows for early warning and prediction of liver failure outcomes, guiding physicians in developing targeted treatment plans, enabling early treatment, and reducing short-term mortality.

The invention relates to the field of animal disease models, and discloses an improved progressive immune checkpoint inhibitor related myocarditis mouse model as well as a construction method and application thereof. The construction method of the model comprises the steps that 0.1 mL of a Freund's complete adjuvant mixed solution is subcutaneously injected into a mouse on the 0th day and the 7th day, and the solution contains 0.25 mg of a mouse cardiac troponin I immunogenic peptide fragment; the method is characterized in that a PD-1 inhibitor and a CTLA-4 inhibitor are jointly injected into a mouse in a caudal vein mode at the frequency of one time every two days from the eighth day, the injection dosage of each drug is 5 mg / kg per time, and the injection process is carried out for 5 times in total. According to the application, cardiac inflammation caused by ICIs drugs is induced through combined use of various reagents, and a disease outcome stage of a patient in the real world is perfectly simulated through dose control and injection method improvement, so that a bedding effect is achieved for clinical research and drug test.

The invention relates to methods for diagnosing, predicting disease development, disease progression and / or disease outcome, predicting susceptibility to treatment, and / or classification in the context of diseases or disorders of the female reproductive tract, in particular endometriosis, wherein biomarkers of Table 1 are determined, e.g. CCL5 and / or NEAT1. The invention further relates to pharmaceutical products for use in patients stratified according to the methods of the invention and to compositions comprising reagents for the detection of the biomarkers of Table 1 for the diagnosis of diseases or disorders of the female reproductive tract.

Provided herein are methods, compounds, and compositions for safely reducing thrombopoietin in a cell or an individual. Such methods, compounds, and compositions maintain platelet count within a safe hemostatic range. Such methods, compounds, and compositions are useful to safely treat, prevent, or ameliorate a disease that can benefit from platelet count reduction in an individual. Such methods, compounds, and compositions are useful for treating or preventing diseases in which thrombopoietin contributes to the presence or activation of platelets contributes to and promotes disease initiation or progression, and / or adversely affects disease outcome.