11 results about "Treatment sequence" patented technology

The invention relates to the technical field of data synchronization, in particular to a digestive system department clinical information acquisition and synchronization system, which comprises a multi-source heterogeneous acquisition module for generating a standardized diagnosis and treatment sequence, a characteristic spectrum construction module for mapping a text and an image into vector nodes and constructing a dynamic diagnosis and treatment characteristic spectrum, the state fingerprint verification module calculates a map fingerprint Hamming distance to position a difference feature node, and the incremental collaborative synchronization module constructs an incremental data packet and sends the incremental data packet to the central server. According to the method, the multi-dimensional characteristic spectrum based on the diagnosis and treatment time sequence is constructed, discrete images and texts are converted into topological association units, heterogeneous data semantic level alignment and integrity verification are achieved, version conflicts and information faults are eliminated, meanwhile, a dynamic hash fingerprint difference comparison strategy is adopted, accurate recognition is achieved, and only substantial change nodes are transmitted; and the network load is reduced, and high real-time consistency and zero-loss circulation of whole-flow information are ensured.

The invention relates to a medication recommendation method and system. The method comprises the following steps: preprocessing original medical data of a current patient into a standardized time sequence diagnosis and treatment sequence; inputting the time sequence diagnosis and treatment sequence and the medical professional knowledge base into a code-doctor-seeing double-level attention model for processing to obtain code-level aggregation features of each doctor seeing and corresponding doctor-seeing-level attention weight, and performing weighted aggregation on the code-level aggregation features based on the doctor-seeing-level attention weight to obtain a code-level aggregation feature; generating a global health representation of the current patient; based on at least one of the multiple medical feature information of the current patient, similar historical cases are retrieved from a case information base to serve as reference cases; and generating and outputting a medication recommendation list for the current patient at least based on the global health representation of the current patient and the medication scheme of the reference case. By adopting the method and the device, the accuracy and the safety of drug recommendation for the current patient can be improved, so that a doctor can be better assisted to make a drug decision.

In information processing device, the information acquisition means acquires patient information, medical professional information, and environment information. The treatment order determination means determines an order of treatment of the patients for each medical professional based on the patient information, the medical professional information, and the environment information.

The application discloses a skin rejuvenation treatment effect texture image analysis method and system, and relates to the technical field of medical image processing, and comprises the following steps: acquiring treatment texture images and illumination collection data of a target object; performing separation operation on the treatment texture images according to a treatment sequence, and performing symmetry consistency evaluation on the illumination collection data and the separation operation result to generate a stable mask graph; respectively performing weighted alignment on the separation operation result before and after treatment according to the stable mask graph, generating a locked texture graph in pairs, and performing symmetry statistics on the locked texture graph to generate a brightness reference graph. According to the scheme, the weighted alignment based on the stable mask graph and the symmetry statistics of the brightness reference graph are used, so that the texture comparison before and after treatment is changed from 'pixel comparison' to 'brightness comparison', the interference of illumination drift on difference calculation is significantly reduced, a normalized texture graph is generated by fusing and correcting illumination collection parameters, and an alignment difference bottom graph is obtained by modulating the stable mask graph.

Systems and methods for treating target tissues include: a preparation sequence for generating acoustic processing pulses to deliver acoustic energy to the target tissue; pausing the generation of acoustic processing pulses after a delay interval; and a treatment sequence for generating a series of acoustic processing pulses to deliver acoustic energy to the target tissue, wherein the treatment sequences are spaced apart by acoustic processing intervals, and the delay intervals are larger than the maximum acoustic processing interval by a predetermined coefficient.

The application relates to the technical field of medical robots and discloses a medical mechanical arm coordination control method and system based on global redundancy optimization, which comprises the following steps: collecting patient head MRI image data, establishing a multi-coordinate system conversion chain, generating a head collision detection grid model to solve a medical safety subset corresponding to each single target point in a target point sequence to be treated; constructing a redundancy configuration transition graph to obtain a global optimal redundancy parameter sequence, and then generating a joint space trajectory; calculating a new target pose which needs to be compensated for the mechanical arm end in the trajectory execution process and estimating a corresponding new medical safety subset, and finally generating fine-tuning joint instructions; through global planning of redundancy transition intersection and real-time constraint of dynamic safety subset, the application effectively eliminates joint motion jumps caused by redundancy parameter mutations, realizes smooth transition of a multi-target point treatment sequence and high-precision stable control in a dynamic following process.

The invention discloses a far-infrared intelligent Dan moxibustion cooperative system based on big data analysis and an intelligent Dan moxibustion bed, and the method comprises the steps: firstly, generating a homogenized acupoint distribution map through heat radiation scanning, combining an analysis algorithm with a physiological model for comparison, precisely marking a thermal anomaly region, and extracting a treatment point coordinate set; secondly, dynamically calculating a temperature gradient curve based on priority ranking and sensor feedback, and optimizing treatment parameters; and finally, fusing distance sensor data and a posture calibration system, determining an accurate treatment distance, and integrating duration control and vector data to form a continuous collaborative treatment sequence, so as to ensure treatment precision and adaptability. According to the method, through integrated innovation of heat energy distribution analysis, dynamic parameter adjustment and posture calibration, the accuracy and personalized adaptive capacity of acupoint treatment are remarkably improved, and an efficient solution is provided for accurate intervention of heat energy abnormity of a human physiological system.

The application relates to a medication recommendation method and system, which comprises the following steps: preprocessing original medical data of a current patient into a standardized time sequence diagnosis and treatment sequence; inputting the time sequence diagnosis and treatment sequence and a medical professional knowledge base into a code-visit two-level hierarchical attention model for processing, obtaining code-level aggregated features of each visit and corresponding visit-level attention weights, weighting and aggregating the code-level aggregated features based on the visit-level attention weights, and generating a global health representation of the current patient; searching for similar historical cases as reference cases from a case information base based on at least one of a plurality of medical feature information of the current patient; and generating and outputting a medication recommendation list for the current patient based on at least the global health representation of the current patient and a medication scheme of the reference cases. The application can improve the accuracy and safety of medication recommendations for the current patient, thereby better assisting doctors in making medication decisions.

This invention discloses a multimodal radiomics-based HDRBT combined with thermal ablation therapy for liver cancer efficacy evaluation system, relating to the field of liver cancer treatment. The system includes: a multimodal image data acquisition module for collecting multimodal image data; a three-dimensional visualization model construction module for reconstructing the three-dimensional structure of the liver tumor, surrounding blood vessels, and bile ducts through image segmentation algorithms and integrating radiomics features to generate a visualization model; a combined treatment plan generation module for integrating HDRBT dosimetric parameters and thermal ablation process parameters, optimizing catheter insertion path, thermal ablation electrode position, and treatment sequence to generate a combined treatment plan; and an efficacy evaluation module for quantitatively analyzing tumor volume changes, ablation boundary integrity, and residual tumor activity through precise registration of multimodal images before and after treatment. This application's solution can address the problems of incomplete thermal ablation and high recurrence rate in hepatocellular carcinoma, providing full-chain technical support for precise clinical application.

This invention discloses a method and system for assessing the risk of hemorrhage in cerebral cavernous malformations. It acquires patient lesion classification data and hemorrhage history, integrates image coding and hemorrhage event characteristics, identifies pseudo-improvement segments, performs compensation corrections to construct a risk feature vector, and extracts the hemorrhage interval rhythm to form an interval marker. The risk feature vector defines the danger level, and evolution markers are obtained based on the danger level. A stratified early warning criterion set is established by combining the interval markers with hierarchical extrapolation. An induction index is determined based on the interaction effect between the interval markers and the danger level, and a propensity correction value is formed through risk trigger mapping and adaptive correction. The propensity correction value is used to review the treatment sequence and assess the intervention safety margin, matching the intervention timing to determine the intervention plan. The early warning criterion set and the propensity correction value are correlated and integrated for time-series extrapolation to form hemorrhage time window parameters. Combined with the intervention plan scenario adaptation, a hemorrhage risk assessment report is generated, providing systematic support for individualized clinical intervention decisions.