4 results about "Intervention measures" patented technology

The invention discloses a nerve-mediated syncope risk prediction method and system, and relates to the technical field of medical evaluation.The method comprises the steps that firstly, units are divided according to patient identity types and syncope scenes in a two-dimensional mode, and then a scene-syncope association model is constructed according to historical syncope records; through multi-dimensional data acquisition, matching of inducement features corresponding to user identity types, locking of associated suspicious syncope scenes, prediction of the risk of user syncope, when the risk exists, intervention measures are provided for the user, the intervention condition is monitored, and corresponding feedback is carried out at the same time, the method can identify multiple syncope scenes and multiple identity types, and the safety of the user is improved. The collaborative risk is quantified, the accuracy of risk level judgment is guaranteed, the prediction precision is greatly improved, early-stage and high-accuracy risk prediction is achieved, scene-identity-intervention association rules are established, the individuation and pertinence of intervention measures are improved, the intervention effect is guaranteed, and therefore the safety of a user is improved.

The present application belongs to the technical field of pressure injury, and particularly relates to a new-born skin injury comprehensive prevention and management system. The present application generates a personalized risk threshold by fusing clinical data and multi-modal physiological parameters, avoids single risk judgment, improves the pertinence and accuracy of prediction, collects data only during a physiological steady state period, effectively reduces noise caused by disease fluctuations or interference factors, improves the stability and reliability of risk parameter calculation, comprehensively automatically executes a risk assessment process, triggers a graded early warning and intervention push in real time when the score exceeds the threshold, greatly shortens the response time from risk identification to intervention, verifies the real-time effect of the intervention measures through an intervention feedback module, realizes closed-loop management of risk discovery, intervention, verification and optimization, reduces missed alarms and invalid interventions, and automatically generates a monitoring curve and historical trends to help medical staff intuitively judge risk change trends and support long-term management and scientific research analysis.

The application discloses a VTE real-time monitoring and intelligent prevention and treatment system and belongs to the technical field of intelligent prevention and treatment, comprising: a baseline construction module, which is used for collecting multi-dimensional VTE parameters, calculating the normal fluctuation range of each parameter to form an initial individual baseline, and constructing an adaptive individual baseline through threshold calibration; a trend identification module, which is used for dynamically setting the length of a sliding window, calculating the trend slope and VTE accumulation bias of VTE, constructing trend constraints and accumulation bias constraints, and determining that there is a continuous abnormal deviation when both constraints are not met at the same time and the length of continuous deviation exceeds a certain time; a time sequence risk prediction module, which is used for calculating the deviation value of each parameter of a target patient, constructing a space-time fusion feature matrix, inputting a time sequence risk prediction model, and outputting a VTE risk probability; and an early warning intervention module, which is used for double determination intervention, setting three-level early warning and intervention measures, calculating an improvement rate to verify the prevention and control effect in real time, and realizing early identification and intelligent prevention and control of VTE.

The invention discloses a neonatal asphyxia risk prediction model construction method and device, which are applied to the field of computer models for disease prediction, and are used for acquiring clinical feature data of a neonatal asphyxia group and a healthy neonatal group, including pregnant mother information, fetus information and other information; performing single-factor analysis on clinical risk factors between the two groups of data, and screening out single-factor predictive variables; and by taking the screened variables as independent variables and taking whether suffocation occurs as dependent variables, carrying out binary Logistic regression analysis by adopting a forward stepwise method, and establishing a risk prediction model. A visual column diagram is drawn according to the prediction model, and the prediction model has good distinction degree and calibration degree through evaluation. According to the method, key independent risk factors are screened from multiple factors through a scientific statistical analysis method, a prediction model beneficial to early clinical recognition of neonatal suffocation high-risk groups is constructed, a basis is provided for timely making individual intervention measures, and the method is of great significance in preventing neonatal suffocation and improving the survival rate of neonates.