6 results about "Baseline level" patented technology

The invention relates to the technical field of image detection, in particular to a multi-modal data video inspection concentration degree analysis and early warning method and system, and the method comprises the steps: collecting face video data, and extracting eye micro-motion features, eyebrow morphological features and forehead myoelectricity visual features in face features; collecting heart rate variability data and galvanic skin response data in the physiological signals; personalized standardization processing is carried out, and Z-score feature vectors relative to the deviation degree of the user's base line level value are obtained through conversion; on the basis of the Z-score feature vector, constructing a time sequence feature vector, inputting the time sequence feature vector into a multi-modal time sequence fusion network for time sequence collaborative mode analysis, and outputting a current concentration degree probability value and a concentration degree prediction value at a future specified time point; and triggering a grading early warning mechanism based on the current concentration degree probability value and the concentration degree predicted value. According to the invention, information complementation is utilized in multi-modal data fusion, so that the robustness and accuracy of state recognition are improved.

The present application relates to the technical field of image detection, in particular to a multi-modal data video inspection concentration analysis and early warning method and system, the method comprising collecting facial video data, extracting eye micro-motion features, eyebrow shape features and forehead muscle television features in facial features; collecting heart rate variability data and skin electricity reaction data in physiological signals; performing individualized standardization processing, converting into Z-score feature vectors of deviation degree relative to user's own baseline level value; based on the Z-score feature vectors, constructing time sequence feature vectors and inputting into a multi-modal time sequence fusion network for time sequence collaborative mode analysis, outputting current concentration probability value and concentration prediction value at a specified time point in the future; triggering a hierarchical early warning mechanism based on the current concentration probability value and the concentration prediction value. The present application utilizes information complementation in multi-modal data fusion, thereby improving the robustness and accuracy of state recognition.

Provided herein is a method for determining molecular response score for use in predictive model.Molecular response score can be used to monitor and guide the administration of treatment to subject.The molecular response score can be generated by a method comprising: for at least one variant among a plurality of variants classified into somatic cells, determining the weighted average of the first variant allele fraction (MAF) and the weighted average of the second MAF based on the first MAF and the second MAF.

This invention discloses a method and device for dynamic blood pressure assessment based on postural transition phases. It identifies postural transitions from postural sensor data and delineates the boundaries of the preparation, transition, and stabilization phases based on individualized reflex delay compensation. It constructs an individualized blood pressure baseline curve based on phased sampling and establishes a phased reference benchmark. It detects a continuous downward trend in the blood pressure deviation sequence and applies individualized rate constraints to form a dynamic trajectory. It removes physiological periodic components using an adaptive rhythm template and determines abnormal fluctuation ranges and completes phased risk assessment based on a joint score of non-rhythmic fluctuation amplitude and duration. It integrates the risk assessment results with the individual baseline level for adaptive weighting based on postural orientation, determines differentiated warning thresholds, and outputs blood pressure change assessment results. This achieves individualized and phased-differentiated accurate assessment of blood pressure abnormalities induced by postural transitions, improving the accuracy and adaptability of orthostatic hypotension risk assessment.

This invention relates to the field of intelligent medical monitoring technology, specifically a pain assessment model based on facial expressions and AI. The model includes: starting from acquired continuous facial image sequences, dynamically detecting and labeling abnormal muscle regions whose activity intensity exceeds an individual's baseline level based on facial muscle anatomy. These abnormal regions are then time-series tracked, their activity intensity evolution trajectory is quantified, and the correlation coefficients of activity changes between different regions are analyzed to construct a multi-region collaborative relationship matrix. The regional activity intensity evolution trajectory data and the collaborative relationship matrix are fused, and processed by a pre-trained pain feature classifier to output a pain probability distribution. This invention improves the accuracy and reliability of pain expression recognition, especially when individual differences and complex expression confusion exist, by performing abnormal detection and dynamic collaborative analysis at the physiological muscle activity level.

The invention relates to the technical field of medical insurance intelligent auditing, and discloses a medical insurance medical document auditing method and system based on a knowledge graph. The method comprises the steps of obtaining evaluation index data and auditing results of an intelligent auditing system in a hospital in different time periods before and after being online, and determining knowledge graph nodes according to data changes; constructing a medical insurance auditing knowledge graph based on the data of each time point and the logic dependency relationship between the nodes; calculating a baseline level value and a change trend value of the evaluation index, and obtaining auditing influence coefficients of the node in different auditing links after the system is online in combination with graph node logic dependence; and screening nodes exceeding a preset threshold value according to the auditing influence coefficient as nodes to be intervened, and generating an optimized knowledge graph for document auditing. According to the method, the knowledge graph is dynamically constructed by comparing the data before and after the system is online, and the node contribution is quantified by using the influence coefficient to realize accurate optimization, so that the adaptive capacity and the intervention efficiency of the auditing system are improved.