53 results about "Treatment Effectiveness Evaluation" patented technology

The invention discloses a personalized tinnitus treatment method based on artificial intelligence, and particularly relates to the technical field of artificial intelligence, and the method comprises the steps: S1, user data collection: collecting user data, and transmitting the collected data to an edge computing node; s2, user data preprocessing: carrying out data preprocessing; s3, sending a medical diagnosis request: collecting medical data, and sending the medical data and the medical diagnosis request to a control center; s4, comprehensive analysis and scheme making, wherein comprehensive analysis is carried out, and a personalized tinnitus treatment scheme is made; s5, decision instruction transmission and scheme execution; and S6, dynamic optimization and feedback: collecting treatment feedback data in real time, obtaining a treatment effect evaluation index, and dynamically adjusting a treatment scheme. By collecting user data and medical data in real time, constructing an artificial intelligence model to judge the tinnitus probability and tinnitus subtype, formulating a treatment scheme, judging the treatment effect and dynamically adjusting according to the treatment effect, the treatment effect of the user is effectively improved.

The invention discloses a human body peripheral blood vessel photoacoustic three-dimensional imaging device and an imaging method thereof, and belongs to the field of blood vessel imaging. Through high resolution and functional monitoring capability of photoacoustic imaging, detailed blood vessel structure and blood flow dynamic information are provided, and early recognition and treatment effect evaluation of common lesions such as diabetic foot and peripheral artery diseases are promoted; meanwhile, a mechanical system is adopted, so that the detection front end with relatively high quality can be borne, and stable operation is realized, and a relatively good photoacoustic imaging result is obtained; the system has a highly stable accurate scanning imaging mode, and is convenient for multiple imaging modes of clinical application; through the arrangement of the imaging water tank and the lifting structure of the imaging water tank, switching of imaging modes in a limited space can be ensured, so that the device can be suitable for the layout of a portal type three-dimensional moving device. The system is expected to promote the portability of equipment, reduce the research and development cost of the equipment, be widely applied to clinical practice and community medical treatment, and improve the disease management level.

The invention discloses a system for treating chronic lumbago through the synergistic effect of massage and whole body vibration training. The system comprises a patient information registration and management module, a chronic pain evaluation module, a treatment effect evaluation module, a data analysis and feedback module, a vibration training control terminal and a massage treatment and guidance module. A patient is guided to complete standardized waist actions, pain scores under various postures are recorded, a main pain area is determined in combination with a Pareto analysis method, an average value and standard deviation model is constructed by using score data in multiple treatments, and normal distribution fitting and curative effect judgment of pain changes are further achieved. Massage and vibration training are linked through the system, data intercommunication is achieved, standardized, intelligent and personalized intervention in the treatment process is achieved, and the rehabilitation efficiency of the chronic lumbago patient is effectively improved. The system has the advantages of complete structure, scientific evaluation, accurate intervention and the like, and is suitable for popularization and application in the fields of rehabilitation medicine and clinical physical treatment.

The invention relates to the technical field of treatment and healing of depression patients, and discloses a depression patient AI treatment and healing interaction and note generation method based on natural language processing, which comprises the following steps: step 1, constructing a natural language processing model; step 2, psychological assessment and emotion analysis; 3, a personalized chemotherapy healing interaction strategy; step 4, a note generation function; and 5, evaluating and feeding back the treatment effect. According to the depression patient AI healing interaction and note generation method based on natural language processing, depression healing is converted into an online reinforcement learning problem, the rehabilitation effect of the patient is taken as an instant reward, an interaction strategy is taken as an action space, the quality of a strategy library is automatically improved through continuous iteration, and compared with static script type dialogue, the method has the advantages that the efficiency is greatly improved; the system can dynamically adjust parameters according to three factors of emotion level improvement, interaction duration and satisfaction, achieves the purpose of'understanding patients more than using ', enables a strategy library to be periodically and globally retrained after a large amount of crowd data is converged, remarkably shortens the single-time healing effectiveness time, and improves the overall rehabilitation efficiency.

A computer-implemented method for processing digital pathology images, the method including receiving a plurality of digital pathology images of at least one pathology specimen, the pathology specimen being associated with a patient. The method may further include determining receiving metadata corresponding to the plurality of digital pathology images, the metadata comprising data regarding previous medical treatment of the patient. Next, the method may include providing the medical images and metadata as input to a machine learning system, the machine learning system having been trained by receiving as input historical treatment information and digital images labeled with a predicted treatment regimen. Lastly, the method may include outputting, by the machine learning system, a treatment effectiveness assessment.

The invention discloses a universal lymphedema measuring scale for upper and lower limbs, relates to the technical field of medical measuring instruments, and provides the following scheme: the universal lymphedema measuring scale comprises a pedal plate for a detector to step on and fix; the leg detection mechanism is arranged at the top of the pedal plate and used for detecting lymphedema of the lower limbs of a detector, and the leg detection mechanism comprises a height measuring rod; the balance plate is fixed at the top of the height measuring rod; and the arm detection mechanism is arranged on the balance plate and is used for performing upper limb lymphedema detection on the detected person. The device can accurately measure the lymphedema degree of the upper and lower limbs, has the advantages of simplicity and convenience in operation, reliable measurement result, high practicability and the like, can be widely applied to the medical field, and solves the problems of non-uniform measurement, high randomness, nonstandard operation and the like in an existing measurement mode; and a reliable measuring tool is provided for diagnosis and treatment effect evaluation of lymphedema.

The application relates to a pain real-time discrimination and treatment effect evaluation system based on EEG microstate monitoring. The system comprises the following modules: a microstate extraction and analysis module which extracts GFP peak topography from EEG signal data, optimizes a template map, calculates the average duration of each microstate category and the like, and outputs a microstate feature parameter set; a pain real-time discrimination module which inputs the microstate feature parameter set into a deep learning model for detection to obtain a detection result containing a pain level; and a treatment effect evaluation module which obtains and compares the microstate feature parameter set before and after treatment, obtains a quantitative treatment effect index, and generates a report containing the index, analysis results and a microstate change trend chart. The system can monitor the pain state of a patient in real time through EEG signal microstate, and can provide objective evaluation indexes about the treatment effect for a clinician by quantifying the dynamic change of the EEG microstate of the patient before and after treatment, so that the scientificity and accuracy of treatment effect monitoring are improved.

The invention provides an image-based tumor treatment effect evaluation method, which belongs to the technical field of treatment effect evaluation, and comprises the following steps: establishing a tumor baseline image feature library and a treatment scheme time window mapping table, and carrying out multi-time-point medical image acquisition in a treatment specificity evaluation time window; obtaining a time sequence medical image data set containing different time points after treatment, processing time sequence data by adopting tumor segmentation software and image quantitative analysis software, dynamically adjusting identification parameters according to a treatment specificity evaluation time window, and establishing a time window parameter mapping relation; tumor volume change features, density change features and boundary definition features are extracted to establish a tumor image feature change matrix, and a comprehensive treatment effect evaluation report is generated according to the image recognition result of the optimal evaluation time point. The technical problem that the treatment effect evaluation precision is insufficient due to the fact that optimal image evaluation time windows of different treatment modes are not matched is solved.

The invention relates to the technical field of big data analysis, and discloses a big data analysis-based outpatient service payment medical insurance data monitoring analysis management system, which comprises a data acquisition module for acquiring outpatient service medical insurance settlement data before and after hierarchical diagnosis and treatment of all medical insurance fixed-point medical institutions in a target area; and the data analysis module is used for acquiring sub-data change amplitudes of the patient flow direction data, the cost benefit data and the disease matching degree data before and after the implementation of the hierarchical diagnosis and treatment in the same target area according to the outpatient medical insurance settlement data before and after the implementation of the hierarchical diagnosis and treatment, and constructing a change amplitude data set. The method comprises the steps of obtaining outpatient medical insurance settlement data before and after hierarchical diagnosis and treatment of a medical insurance fixed-point medical institution in a target area, obtaining a change amplitude data set and a difference value data set according to the outpatient medical insurance settlement data, completing correction, and performing comprehensive evaluation according to the corrected data to obtain a hierarchical diagnosis and treatment effectiveness evaluation result.

This invention discloses a seismic treatment effectiveness evaluation system for thick loess sites, belonging to the fields of geotechnical engineering and earthquake engineering technology. The system comprehensively evaluates the seismic treatment effect by acquiring dynamic characteristic parameters and seismic response parameters of thick loess sites before and after seismic treatment. The system includes a site foundation parameter acquisition module, a dynamic characteristic parameter acquisition module, a loess dynamic degradation characteristic analysis module, a seismic response simulation module, a seismic treatment effectiveness quantification module, and an evaluation result output module. Specifically, it analyzes the loess dynamic degradation characteristics based on parameters such as shear wave velocity, shear modulus, and damping ratio, and acquires seismic response results such as surface acceleration, shear strain, and site amplification factor under the same seismic motion input conditions. By normalizing and weighting the dynamic degradation improvement index and the seismic response improvement index, a comprehensive seismic treatment effectiveness index is constructed, enabling quantitative evaluation and classification of seismic treatment effectiveness.

The application discloses a kind of massage and whole body vibration training synergistic effect treatment chronic low back pain system, including patient information registration and management module, chronic pain assessment module, treatment effect assessment module, data analysis and feedback module, vibration training control terminal and massage treatment and guidance module;Through guiding patient to complete standardization waist action and record each posture under the pain score, determine main pain area in combination with Pareto analysis method, and utilize the score data in multiple treatments, construct mean and standard deviation model, and then realize the normal distribution fitting of pain change and curative effect determination;Massage and vibration training are linked through system, data intercommunication, realize the standardization of treatment process, intelligent and personalized intervention, effectively improve the rehabilitation efficiency of chronic low back pain patient.The application has the advantages of complete structure, scientific evaluation, precise intervention, etc., and is suitable for the popularization and application in the field of rehabilitation medicine and clinical physical therapy.

The invention provides a living single cell multi-modal in-situ detection analysis method and a treatment scheme evaluation optimization method, and relates to the technical field of precision medical treatment, and the method comprises the following steps: obtaining multi-modal data of a living single cell to be detected in situ; the multi-modal data comprises at least two of the following data: electrical impedance data of a living single cell to be detected under a plurality of frequencies, Raman spectrum data of the living single cell to be detected, and image data of the living single cell to be detected; the frequency is the frequency of an alternating current signal applied to the cell through the electrode; extracting multi-modal dynamic characteristics of the living single cell to be detected from the multi-modal data by adopting a combined modal data analysis method; wherein the combined modal data analysis method comprises a cell electrophysiological analysis method, a cell multi-molecular spectroscopy analysis method and a cell image analysis method. Therefore, the multi-modal dynamic measurement method is utilized to obtain multiple groups of dynamic characteristic information of the cells, and accurate treatment effect evaluation and process optimization can be realized.

The invention discloses an integrated recognition and detection system based on electroencephalogram signals and brain function near-infrared signals, and particularly relates to the technical field of medical diagnosis, which comprises a signal acquisition module, a main control module and PC (Personal Computer) upper computer software. Data processing and transmission are carried out through the main control module, display, analysis and real-time monitoring of the data are achieved in cooperation with PC upper computer software, detailed brain wave shape and near-infrared brain function imaging results can be provided, early diagnosis and intervention can be assisted, biomarkers in EEG and fNIRS data can be extracted through a classification recognition algorithm, and the accuracy of diagnosis and intervention is improved. The method helps to identify potential features, evaluates the severity of the illness state in combination with a clinical information database, and supports the formulation and monitoring of a personalized rehabilitation treatment scheme, thereby providing real-time and accurate diagnosis and treatment effect evaluation for a child patient.

The invention provides an ear vagus nerve stimulation device and system based on artificial intelligence control, and relates to the technical field of artificial intelligence and medical equipment, and the method comprises the steps: obtaining multi-source data of a corresponding tinnitus patient; preprocessing the multi-source data based on a statistical method to obtain preprocessed multi-source data; performing feature extraction on the preprocessed multi-source data based on a random forest feature selection algorithm to obtain corresponding key feature data; historical key feature data are obtained, a tinnitus prediction model and a treatment effect evaluation model are constructed based on a recurrent neural network and a long-short term memory network, and then a tinnitus prediction result and treatment effect evaluation are obtained; the tinnitus prediction model and the treatment effect evaluation model are optimized; based on the deep Q network of the reinforcement learning algorithm, according to the trained tinnitus prediction model and treatment effect evaluation model and the real-time data of the patient, a personalized treatment scheme is generated, then a stimulation parameter adjustment instruction is obtained, and the accuracy is improved.

This invention provides a sample pretreatment kit and its application for the simultaneous detection of Aβ40, Aβ42, and lencanezumab, belonging to the field of biodetection technology. The kit includes: mixed magnetic beads, internal standard solution, trypsin digestion solution, enzyme digestion enhancer, and ammonia; the mixed magnetic beads are composed of protein A magnetic beads and streptavidin magnetic beads; the internal standard solution is composed of… 15 N-labeled Aβ40, 15 This kit consists of N-labeled Aβ42 and lencanezumab internal standard peptides. The pretreatment kit eliminates the need for anti-IgG1 antibodies, requiring only Protein A for detection, thus shortening sample processing time, greatly simplifying the sample handling process, and increasing throughput. The kit can simultaneously detect Aβ40, Aβ42, and lencanezumab, providing more reliable data support for clinical diagnosis and treatment efficacy evaluation, and significantly promoting the development of companion detection technologies for Alzheimer's disease biomarkers and therapeutic drugs.

1. Name of the product in this design: Interactive graphical user interface for an oxygen chamber therapy effect evaluation system for electronic devices. 2. Intended use of this design: for use in an electronic device. 3. The key design feature of this product is its graphical user interface. 4. The image or photograph that best illustrates the design's key features: the front view. 5. Other orthographic views and perspective views are omitted. 6. Purpose of the graphical user interface: To display the main workflow and content of the hyperbaric oxygen therapy department. 7. Description of the changing states of the graphical user interface: The main view is the login interface; Figure 1 shows the interactive interface displayed after entering the correct username and password in the main view and clicking the "Login to System" button; Figure 2 shows the interactive interface displayed after clicking "Admission Treatment Management" in Figure 1; Figure 3 shows the interactive interface displayed after clicking "First Chamber" in Figure 2; Figure 4 shows the interactive interface displayed after clicking "Treatment Records" in Figure 3.

The invention discloses a serum protein combination marker for monitoring liver fibrosis reversion of chronic hepatitis B patients after long-term treatment and application thereof. The invention first discloses a serum protein combination marker for monitoring liver fibrosis reversion of chronic hepatitis B patients after long-term antiviral treatment, and the serum protein combination marker comprises SERPINA7, CD163 and CFHR4. The invention further discloses application of the marker in preparation of products for monitoring liver fibrosis reversion of chronic hepatitis B patients after long-term treatment. By detecting the content ratio of the serum protein combination marker before and after long-term antiviral treatment of chronic hepatitis B patients, the liver fibrosis reversion state can be accurately monitored, and the performance is obviously superior to that of instantaneous elastography and conventional noninvasive indexes. In addition, the serum protein combined marker is based on blood detection, is noninvasive and convenient, and can provide a reliable basis for treatment effect evaluation and clinical decision.

The application discloses a kind of human peripheral blood vessel photoacoustic three-dimensional imaging device and imaging method thereof, belong to blood vessel imaging field.The application provides detailed blood vessel structure and blood flow dynamic information by high resolution and functional monitoring ability of photoacoustic imaging, promote early identification and treatment effect evaluation to common pathological changes such as diabetic foot and peripheral arterial disease;Meanwhile, the application adopts mechanical system, and the detection front end of higher quality can be carried and stably operated, to obtain better photoacoustic imaging result;The application has highly stable precision scanning imaging mode, and various imaging modes are convenient for clinical application;Through the arrangement of imaging tank and its lifting structure, it is ensured that the switching of imaging mode can be applied in limited space, so as to be suitable for gantry type three-dimensional mobile device layout.The application is expected to promote the portability of equipment, reduce equipment development cost, be widely applied in clinical practice and community medical treatment, and improve disease management level.

The application discloses a transcranial magnetic stimulation method and device based on digital twin data-mechanism driving. The application realizes the synchronous evolution of the brain function model and the real brain state information by using the field self-adaptive brain function model synchronous evolution method, thereby reducing the lagged perception of the patient brain state change information in the treatment process, adjusting the coil parameters according to the treatment effect evaluation results, realizing the mechanism-driven closed-loop control, and using the dynamic simulation results to perform the stimulation scheme virtual pre-performance, realizing the closed-loop treatment strategy optimization of the virtual-real bidirectional feedback, and solving the technical problems that the open-loop targeted stimulation method has the lagged nature for the treatment effect evaluation, and cannot make the optimization adjustment in time for the stimulation effect. In addition, the real-time target point registration method based on visual servo is used to realize the space position information registration of the virtual head model and the patient head, thereby realizing the target point virtual-real space position information closed-loop interaction, and ensuring that each pulse stimulation can accurately target the stimulation point.

To objectively and quantitatively evaluate the effectiveness of alternative medical treatments such as manual therapy and osteopathic therapy. [Solution] A treatment effect evaluation system (10) for evaluating the effect of treatment as alternative medicine by a practitioner (1) on a patient (2), comprising: a terminal device (30) including a data collection unit that connects to each device constituting a sensor group (20) and collects biometric data and lifestyle data of the patient, as well as environmental data related to the treatment environment for the patient; an analysis device (40) including an analysis unit that evaluates the effect of the treatment by analyzing the biometric data, lifestyle data and environmental data using AI; and the terminal device (30) further including an output unit that outputs the analysis results by the analysis unit.

The invention relates to the technical field of internet medical treatment, and discloses a new auxiliary immunotherapy effect evaluation method and system, and the method comprises the steps: dividing multi-modal image data into a plurality of fusion groups according to a correlation analysis result of the obtained multi-modal image data, carrying out the preliminary fusion of the multi-modal image data in each fusion group, and obtaining a fusion result; obtaining a corresponding first fusion feature map; performing spatial attention mechanism processing on the first fusion feature map and the multi-modal image data of the same fusion group to perform weighted fusion so as to obtain a second fusion feature map of each fusion group; and performing splicing fusion on a third fusion feature map obtained by performing cross fusion on all the second fusion feature maps by adopting a multi-head cross attention algorithm and all the second fusion feature maps to obtain a fourth fusion feature map, and inputting the fourth fusion feature map into the trained treatment effect evaluation model to obtain a new auxiliary immunotherapy effect evaluation result. According to the method provided by the invention, the accuracy of evaluating the neoadjuvant immunotherapy effect is effectively improved.

The invention discloses a method and device for determining a traditional Chinese medicine common disease diagnosis model based on individual sampling, and the method comprises the steps: obtaining the diagnosis data of a traditional Chinese medicine for each first patient in a first historical time period for each traditional Chinese medicine corresponding to a target common disease; training according to the diagnosis data of each first patient to obtain a common disease diagnosis model corresponding to the traditional Chinese medicine; for the common disease diagnosis model corresponding to each traditional Chinese medicine, determining treatment data of each second patient based on the common disease diagnosis model in a second historical time period; determining a treatment effect evaluation score of the common disease diagnosis model according to the treatment data of each second patient; and according to the treatment effect evaluation score of each common disease diagnosis model, selecting the common disease diagnosis model with the highest treatment effect evaluation score, and determining the selected common disease diagnosis model as a target common disease diagnosis model corresponding to the target common disease. The accuracy of traditional Chinese medicine diagnosis based on the target common disease diagnosis model is ensured, and medical skill inheritance of the target traditional Chinese medicine is realized.

The invention discloses a treatment effect evaluation method and system suitable for an HBO oxygen cabin, and relates to the technical field of medical data analysis, and the method comprises the steps: carrying out the recognition linkage of an HIS system through a wrist strap before a patient enters the cabin, collecting the medical advice, diagnosis and multi-modal physiological and subjective scoring data of the patient, and generating an initial treatment vector after standardization; the method comprises the following steps: constructing a curative effect triple based on a medical ontology, generating a semantic map embedding vector by adopting a TransE model, embedding and splicing each treatment data and a map, constructing a time map structure, modeling a patient curative effect evolution trajectory by utilizing a Time-GCN model, outputting a final state representation vector, and calculating a final curative effect score. According to the method, the whole process of curative effect evaluation is intelligentized, structured and traceable, curative effect evolution characteristics can be effectively captured, and a scientific basis is provided for personalized clinical decision making.

The invention discloses a method for establishing a target immunity treatment effect evaluation model for a liver cancer patient, and the method specifically comprises the following steps: S1, obtaining an arterial phase MRI image of the HCC patient, and carrying out the preprocessing; s2, inputting the preprocessed MRI image into a 3D-Unet network model for training so as to construct an automatic liver tumor segmentation model; s3, inputting an MRI image of an HCC patient receiving target immunotherapy into the 3D-Unet network model to obtain a liver tumor area image, and inputting the liver tumor area image into the 3D-CNN model to learn image features; and S4, fusing the image features extracted from the MRI sequence data by the 3D-CNN model with the clinical features extracted by the Transform module, constructing a multi-modal network model, outputting a dichotomy result of the target immunotherapy effect, and obtaining a model for predicting or evaluating the target immunotherapy effect of the HCC patient. According to the method, automatic segmentation of the liver and tumor areas is realized through the two-stage 3D-Unet network model, the segmentation result is accurate and smooth, and the problems of errors and time consumption caused by manual sketching are effectively reduced.

The invention relates to application of exosome protein in preparation of products for diagnosis, treatment and prognosis evaluation of cerebral infarction diseases. The exosome is efficiently separated from peripheral plasma of a cerebral infarction patient; carrying out proteomics analysis on the separated exosomes, and screening proteins with significant difference in the plasma exosomes in the acute stage and the recovery stage of cerebral infarction; and then respectively verifying the influence of the screened exosome protein on monocyte differentiation, inflammatory response and chemotactic ability. Finally, the screened differential proteins comprise RL27A, SPTCS, CCT2 and SEPP1 (single nucleotide polymorphism 1). By monitoring the change of the exosome protein, an important basis can be provided for disease course management and treatment effect evaluation of cerebral infarction patients. In addition, the functional verification result of the specific exosome protein provides theoretical support for development of new therapeutic targets and drug delivery systems, and possibly provides a new strategy for intervention and treatment of cerebral infarction.

This invention belongs to the field of medical image processing, and specifically relates to a multimodal medical image registration method based on multi-scale prototype-guided dynamic convolution. The method includes: inputting a fixed medical image and a moving medical image into a multi-level encoder, performing upsampling at each level, and outputting a feature map of one scale at each level; in a multi-level decoder matched with a decoder, performing upsampling from level N to level I, and fusing the deformation field of level I with the moving medical image to obtain the registered image. This invention does not rely on MLP or Transformer long-distance dependency modeling, ensuring registration accuracy while also considering inference efficiency. It can provide high-precision spatial registration support for key tasks such as clinical lesion localization, multimodal data fusion, and treatment effect evaluation, and has significant clinical application value and promising prospects for widespread application.

The invention relates to a transcranial electrical stimulation system and method, and relates to the technical field of transcranial electrical stimulation. According to the specific technical scheme, a model building module is used for building a transcranial electric field simulation model according to head image data of a patient and marking a target area and an electric field intensity threshold value; the initial point location arrangement module is used for calling a simulation model to screen an initial electrode point location; the transcranial electrical stimulation execution module is used for applying stimulation according to the initial simulation parameters; the electroencephalogram signal acquisition module is used for acquiring electroencephalogram signals before and after stimulation; the signal processing and evaluation module is used for extracting electroencephalogram time-frequency domain characteristic parameters and obtaining a treatment effect evaluation result; the closed-loop optimization module is used for dynamically adjusting electrode point positions and simulation parameters according to an evaluation result, performing iterative execution until a preset requirement is met, and determining an optimal treatment electrode point position; and the output module is used for outputting the optimal treatment electrode point position. According to the invention, the treatment effect of transcranial electrical stimulation can be improved.

The present invention provides methods for using waste effluent biofluids in cell culture assays as all or part of the cell culture microenvironment. Methods of the invention contemplate that biofluids typically regarded as waste may be used in cell-based assays to achieve a cell culture microenvironment that provides a novel understanding of cellular response.

This application relates to a method and apparatus for deep methylation sequencing assisted by a machine learning classifier of methylation patterns, which allows for sequencing at dilutions down to 10-10. ‑4 This application describes a methylation sequencing method that can detect the presence and / or abundance of low-frequency ctDNA in a sample, potentially offering advantages in cancer screening and treatment efficacy evaluation.