65 results about "Treatment management" patented technology

The invention discloses a digital intelligent tumor prevention and treatment management platform and management method, and relates to the technical field of intelligent medical treatment, and the method comprises the steps: collecting the multi-modal data of a patient in real time, carrying out the standardized cleaning and space-time alignment processing, and generating a space-time tagging data set; inputting the multi-modal joint feature representation into an anti-fact inference engine, simulating potential effects under intervention of different treatment schemes, calculating individual processing effects, and generating an anti-fact rehabilitation suggestion set; according to the anti-fact rehabilitation suggestion set, a dynamic causal enhancement decision model is constructed, real-time physiological data feedback of the patient is continuously received through a near-end strategy optimization algorithm, and a treatment scheme is dynamically adjusted. According to the method, through multi-modal data space-time alignment and feature fusion, in combination with a tumor biological mechanism and a machine learning algorithm, the accuracy and clinical credibility of individualized tumor treatment scheme recommendation are remarkably improved.

Computer-implemented methods of predicting the QTc of a subject in response to administration of QTc prolonging drugs, especially those that are dose adjusted for renal function, such as antiarrhythmic drugs. Included is a method of administering an antiarrhythmic drug to a subject, comprising: providing as inputs into a treatment management application i) Baseline QTc and ii) at least a Creatinine Clearance, Weight, Age, Sex, or Heart Rate; the treatment management application providing as an output one or more predicted QTc or predicted QTc range for the subject expected from administration of a 1-5 hour IV dose, alone or followed by one or more oral doses, of an antiarrhythmic drug to the subject; and upon the one or more QTc or QTc range being within an acceptable range, administering the 1-5 hour IV dose to the subject optionally followed by administering one or more of the oral doses to the subject.

The invention relates to a smart hospital collaborative diagnosis and treatment management method and system, and the method comprises the steps: receiving the appointment registration information of a patient, building a data mapping relation with a hospital information system based on the appointment registration information, and generating a corresponding treatment identifier; after the patient arrives at the hospital, information of the sign-in patient is collected, a sign-in sequence is established, and according to appointment registration information and diagnosis and treatment service data parameters corresponding to the sign-in patient, a treatment serial number is dynamically distributed and a waiting prompt is pushed; after the doctor receives the diagnosis, generating an examination item list based on the preliminary diagnosis information input by the doctor, obtaining the real-time state and queuing data of equipment required by each examination in the examination item list, constructing an execution time window of examination items, generating an optimal examination sequence, and pushing an examination guide path to the patient terminal; and after the patient finishes seeing a doctor, generating a personalized propaganda and education task list according to the diagnosis and treatment information of each stage, and pushing the personalized propaganda and education task list to the patient terminal. The method has the effect of improving the hospital operation efficiency.

The invention relates to the technical field of hepatitis diagnosis and treatment management, and discloses a block chain-based hepatitis patient full-period management method. The method comprises the following steps: creating a patient identity chain in a block chain network, and storing patient registration data and initial diagnosis information; full-cycle diagnosis and treatment data of a patient are obtained and divided into clinical examination, iconography, medication records and life sign monitoring data. Performing multi-dimensional cleaning on the clinical examination data to generate a standardized data set; inputting the iconography data into a pre-trained hepatitis feature extraction model, and outputting a liver injury feature set; verifying the integrity of the medication record, and generating a non-tampering medication time sequence chain; comparing the life sign monitoring data with preset health reference parameters to generate a sign deviation coefficient set; according to the method, data safety and traceability are guaranteed through the block chain, diagnosis and treatment data quality is improved through multi-dimensional data processing, patient privacy is protected, and reliable support is provided for full-period management of hepatitis patients.

The invention relates to the technical field of wastewater treatment management, and discloses an industrial domestic wastewater fine treatment process management method, which comprises the following steps of: accessing an online / offline data source, and finishing time synchronization and data cleaning; state estimation and soft sensing are carried out; constructing a data quality score and anomaly / drift detection; describing a process topology and a material / energy flow by using a directed graph, defining a unified constraint template, and compiling compliance knowledge into executable constraints; mechanism and data driving are coupled at a unit level, combined propagation is carried out at a process line level, and federated migration and parameter aggregation are carried out at a plant station group level; a Pareto strategy is optimized and generated under the goals of effluent indicator, energy consumption, chemical consumption, sludge, carbon strength and maintenance risk. Under the condition that hardware transformation is not needed, operation toughness and performability can be enhanced, the risk that manual adjustment participates in misoperation is reduced, trans-factory multiplexing and governance transparency is improved, and continuous adaptation and compliance closed loop of a strategy are kept under disturbance.

The present disclosure provides a method and a system for respiratory treatment management. The method is implemented by a cloud platform. The method may comprise obtaining, based on a user terminal, at least one of user basic data, basic data of one or more respiratory devices, usage data of the one or more respiratory devices, or respiratory treatment data of a first subject. The user basic data may include basic data of the first subject or basic data of a second subject, and the respiratory treatment data may be obtained from a first monitoring device. The method also comprises generating target information based on at least one of the user basic data, the basic data of the one or more respiratory devices, the usage data of the one or more respiratory devices, or the respiratory treatment data; and sending the target information to the user terminal.

This invention belongs to the field of biomedicine and specifically relates to a method and kit for enriching circulating tumor cells (CTCs) in liver cancer using GPC3 in combination with MERTK. This method combines MERTK with traditional markers such as EpCAM, vimentin, and GPC3 to capture circulating tumor cells in liver cancer, achieving improved enrichment of CTCs. This method and its accompanying kit are widely applicable to early screening of liver cancer, postoperative recurrence monitoring, metastasis risk assessment, and personalized treatment management, and has promising prospects for clinical translation.

Described herein are methods and compositions related to methylation-based determination and characterization of subjects afflicted with various stages of cancer, including lung cancer and non-small cell lung cancer (NSCLC). Osimertinib is one of the most common precision therapies in non-small cell lung cancer but nearly all patients eventually progress due to somatic mutations and cellular plasticity that bypass the treatment. Defining the cellular plasticity state with epigenetics will help physicians know when to switch therapies.

The invention relates to the technical field of medical treatment, in particular to a chronic infectious disease patient management system, which comprises a registration module used for registering identity information, body information, chronic infectious disease type information, chronic infectious disease condition information and other medical history information of a patient; the information database is used for storing disease condition characteristic data, historical treatment scheme data and precautions data of the chronic infectious diseases; the management platform comprises a doctor work station, a patient information station and a feedback module, and the doctor work station is used for obtaining cooperative information of a treatment scheme; the patient information station is used for generating a medicine taking scheme, a doctor seeing scheme and life precautions, and data of the patient information station is sent to the patient terminal, so that a patient obtains treatment and life related information; and the feedback module is used for inputting discomfort information of the patient. The treatment management efficiency of a hospital on the chronic infectious disease patient can be improved, and the chronic infectious disease patient can feed back own conditions in time.

This invention discloses a comprehensive wastewater treatment management system and method, belonging to the field of wastewater treatment technology. The method acquires historical water quality parameter sequences and real-time process parameters for each monitoring node; performs phase space reconstruction on the historical water quality parameter sequences to obtain the attractor trajectory matrix of each node; calculates the maximum Lyapunov exponent difference between nodes and constructs a dynamic correlation matrix; uses the dynamic correlation matrix to drive virtual particles to randomly walk in the node space, with the movement probability determined by the local entropy of the current node's attractor trajectory matrix; inputs the walking trajectory sequence into a deep neural network based on a residual structure to output the water quality exceedance risk index for each node at future times; and adjusts the operating parameters of the wastewater treatment equipment based on the risk index. This application can dynamically capture the nonlinear correlation characteristics between nodes, improving the accuracy and timeliness of risk prediction for wastewater treatment systems.

The invention relates to the technical field of tracing, and discloses a data-driven quality tracing and exception handling management and control method. The method comprises the steps of constructing a data source system covering the whole link from raw material purchasing to terminal delivery, collecting key quality data, converting the key quality data into standardized data assets through a unified format and a coding specification, and storing the standardized data assets into a quality tracing database. According to the method, a full-link data source system covering raw material purchasing to terminal delivery is constructed, unique identification and association of data of raw materials, equipment, products and the like are achieved in combination with a hierarchical association coding system, the problem of data islands in traditional management and control is thoroughly solved, when quality abnormity occurs, full-chain data can be rapidly penetrated through by means of a graph database association model, and the data quality is improved. According to the method, the abnormal source is accurately positioned, the completeness of the traced link reaches 100%, compared with a traditional manual traceability mode, the efficiency is improved by more than 80%, and the batch quality problem expansion caused by untimely traceability is avoided.

According to various embodiments of the present invention, disclosed is a method for providing a user interface-based orthodontic treatment management service. The method may comprise the steps of: obtaining patient registration information; obtaining orthodontic treatment management information of a patient corresponding to the patient registration information; and displaying a treatment schedule of the patient on a calendar included in each of a patient UI and a doctor UI on the basis of the orthodontic treatment management information.

The invention discloses a deep learning auxiliary prevention and treatment management platform for latent tuberculosis infection, and relates to the technical field of latent tuberculosis infection auxiliary prevention. Comprising a data acquisition and dynamic monitoring module, a data preprocessing and organization module, a conflict feature extraction and analysis module, a deep learning conflict evaluation module and a dynamic weight adjustment and optimization module, and it is ensured that each input can be dynamically monitored in the data fusion process, so that basic data is provided for subsequent conflict detection, feature extraction and intelligent evaluation. According to the method, multi-modal data fusion parameters are monitored in real time, conflict features are extracted, data source conflicts are intelligently evaluated by means of a deep learning model, the weight is dynamically adjusted, and the data fusion process is optimized. According to the scheme, the risk assessment accuracy of latent tuberculosis infection is improved, misdiagnosis and missed diagnosis are avoided, and precise medical treatment and personalized treatment implementation are promoted.

The invention discloses a hypertension prediction and diagnosis and treatment management system based on artificial intelligence and big data analysis, and the system comprises a hierarchical diagnosis and treatment decision model module which constructs a patient grouping and hierarchical diagnosis and treatment decision model based on historical data; the big data diagnosis and treatment scheme module is used for matching the model and generating a big data diagnosis and treatment scheme; the machine learning diagnosis and treatment scheme module generates a machine learning diagnosis and treatment scheme through a machine learning model by using the time sequence data; the diagnosis and treatment scheme fusion module fuses the two schemes to generate a final diagnosis and treatment scheme; and the diagnosis and treatment suggestion output module outputs a complete diagnosis and treatment report containing decision basis. According to the method, abnormal output is effectively filtered by fusing a big data statistical rule and machine learning individual recognition, the accuracy and reliability of diagnosis and treatment suggestions are improved, and meanwhile, the interpretability of the scheme and the doctor-patient trust and adaptability are enhanced by providing a decision basis.

The application discloses a kind of information management method and related equipment for thyroid cancer postoperative iodine 131 treatment patient.It comprises: based on the treatment management data of patient, scheduling model is constructed with patient waiting time, medical interaction cost and isolation bed vacancy time as optimization target, and bed capacity constraint, clinical urgency constraint, radiation protection constraint and medical availability constraint are established;Based on the scheduling model and the constraint condition, the joint optimization of patient reservation admission batch, isolation bed allocation and medical communication task is carried out, and the treatment scheduling result is generated;In the case where patient temporary adjustment, bed state change or iodine 131 treatment preparation abnormality is monitored, the treatment scheduling result is dynamically rearranged, so as to execute patient reminder, treatment connection and follow-up management according to the treatment scheduling result after rearrangement.It can solve the problems of low efficiency of reservation and resource coordination, fragmented medical records and lack of dynamic tracking mechanism in traditional information management mode.

The invention relates to the technical field of treatment management, in particular to a comprehensive plastic treatment management system which comprises a hyaluronic acid coordinate prediction module, a current hyaluronic acid coordinate detection module, a coordinate parameter calculation module and a recovery time prediction module. And then predicting the prediction time of restoring hyaluronic acid to the prediction coordinate in the hyaluronic acid coordinate prediction module through the deviation value and the recovery speed, along with continuous input of new review coordinates, namely generation of new change values and deviation values, the module can dynamically update the prediction time, and after each review, the recovery speed is calculated again and the deviation value is adjusted again, so that the recovery speed of hyaluronic acid is recovered to the prediction coordinate in the hyaluronic acid coordinate prediction module. Therefore, the prediction time is corrected, the prediction result is closer to the actual recovery process, prospective information is provided for doctors, and the doctors can plan treatment intervention measures in advance.

An artificial intelligence enabled advanced treatment management system (AI-ATMS) is configured to improve inter-actions and outcomes from a multidisciplinary patient care team. The AI-ATMS includes advanced integration with an artificial intelligence system with access to federated databases. The AI-ATMS is configured for the real-time engagement with the patient-treatment team in a manner that provides the patient-treatment team with context-related data elements, while also permitting the patient-treatment team with the ability to train the AI-ATMS during the engagement. The AI-ATMS may be for treating a cancer or other medical condition.

A method provides a palatal expansion treatment management and visualization system. The method includes receiving data of a craniofacial structure of a patient; identifying one or more parameters corresponding to a palatal expansion treatment plan for the patient; processing the data of the craniofacial structure of the patient and the one or more parameters to generate a visualization of a predicted outcome of the craniofacial structure affected by the palatal expansion treatment plan; and providing, for display in a user interface of a user device, the visualization of the predicted outcome.

According to various embodiments of the present invention, disclosed is a method for providing a user interface-based orthodontic treatment management service. The method may comprise the steps of: obtaining patient registration information; obtaining orthodontic treatment management information of a patient corresponding to the patient registration information; and displaying a treatment schedule of the patient on a calendar included in each of a patient UI and a doctor UI on the basis of the orthodontic treatment management information.

The embodiment of the utility model discloses a diagnosis and treatment management machine. According to one specific embodiment, the diagnosis and treatment management machine comprises a machine body frame, an electronic equipment main body, a display, a controller, a loudspeaker, a blood pressure detector, an infrared camera shooting part, a respiration detection part and a power supply part; the machine body frame is provided with at least two platform components; the peripheral interface area is provided with at least one peripheral interface hole, and the electronic equipment main body and the power supply part are placed in the peripheral interface area; the display is placed in the display placing groove; the infrared camera part is placed above the display; the controller is placed in the controller placing groove; the blood pressure detector and the respiration detection part are respectively placed on the two platform parts; the loudspeaker is placed in the loudspeaker placing groove; and a part replacement placing groove is formed in the part replacement area of the machine frame. According to the embodiment, inspection equipment is integrated, so that the inspection is more systematic, and the base coverage rate is improved.

The invention discloses a polysleep monitoring-electroencephalogram and AI combined noninvasive nerve regulation and control system, which comprises a signal acquisition unit, a signal processing unit, a phase estimation unit, an event gating unit, an AI control and reinforcement learning unit, a delay compensation unit, a multi-modal stimulation unit, a safety isolation and power supply unit and a digital twinborn management unit, all the units form a double-time-scale closed loop through data and control signals, electroencephalogram phase locking and individualized nerve regulation and control are achieved, and closed loop, individualized and traceable regulation and control of the nerve network rhythm are achieved through hardware-level time synchronization and delay compensation, a multi-mode unified driving framework, event gating and AI reinforcement learning combination and digital twinborn treatment course management.

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.

A wastewater treatment management system including a plurality of monitoring stations, a treating station for introducing a treating agent to wastewater, and a principal processing facility for controlling a dose of the treating agent. A system configured to treat a wastewater stream collection system including a source of a treating agent, a metering valve, a sensor, and a controller operatively connected to the metering valve and the sensor. A non-transitory computer-readable medium including instruction that instruct a controller to perform a method of controlling addition of a treating agent into a wastewater stream collection system. A controller for a system configured to treat odor and control corrosion in a wastewater stream collection system that is operatively connectable to a metering valve for administering a treating agent to a wastewater stream collection system.

To provide a clinical management device, a clinical management method, and a clinical management system that facilitate robust clinical prediction and treatment management in consideration of a wide range of personal health factors.SOLUTION: The clinical management device 210 receives a user input query 310 and a set of user health data 312 at an input processing unit 222, identifies a target machine learning model that achieves a correlation threshold with respect to a set of user health features included in the user health data, generates a set of predictive outcome data including an aggregate prediction score and a set of recommended actions associated with the set of user health data, and outputs the set of predictive outcome data in response to the user input query.SELECTED DRAWING: Figure 3

The application provides a chronic lateral ankle instability intelligent diagnosis and treatment management system based on multidisciplinary cooperation, which comprises an intelligent diagnosis module, a multidisciplinary cooperative diagnosis and treatment module, a diagnosis and treatment monitoring module and a feedback optimization module; the intelligent diagnosis module is used for providing patient diagnosis basic characteristics in combination with individual pathological information of the patient; the multidisciplinary cooperative diagnosis and treatment module is used for realizing multidisciplinary cooperative individual diagnosis and treatment scheme making based on the patient diagnosis basic characteristics; the diagnosis and treatment monitoring module is used for monitoring the execution process of the individual diagnosis and treatment scheme; and the feedback optimization module is used for feeding back and optimizing the individual diagnosis and treatment scheme making in combination with diagnosis and treatment execution feedback information. The application generates individualized and self-iterative diagnosis and treatment decisions by taking multidisciplinary cooperation and result evaluation and optimization as cores, so that the curative effect and compliance are improved, the rehabilitation cycle is shortened, and the recurrence and complication risks are reduced under the premise of safety and compliance.

The present application relates to a kind of vascular inflammation prediction method based on knowledge guide and intervention-response drive, belong to artificial intelligence and medical cross technical field.It includes the following steps: acquisition multivariate physiological measurement sequence, completes missing value preprocessing using treatment-aware time series linear interpolation;Physiological and treatment sequence are explicitly decoupled into short-term acute path and long-term cumulative path, respectively through exponential decay model, low-pass filter modeling and are fused by gate mechanism, obtain treatment dynamic representation;Heterogeneous dynamic graph is constructed by fusing medical priori and data learning, executes graph convolution update node representation after treatment modulation adjacency matrix;Finally, the representation of treatment dynamics and graph enhancement is fused, and the TBR prediction value is output by attention weighting and time point specific regression.The present application can effectively separate acute and chronic treatment effects, inject clinical knowledge constraints, and is suitable for tumor survivor cardiovascular risk stratification, vascular toxicity mechanism analysis and personalized diagnosis and treatment management.

The present application relates to the technical field of medical records, in particular to a stoma treatment management system based on a timeline, which comprises a starting collection module, a content arrangement module, a sequence integration module, an identity comparison module and an intermittent presentation module.In the present application, a time difference identification mechanism is established by extracting the image generation time and the submission time, data binding is completed by combining the image number and the identity information, semantic merging is achieved by integrating the excrement description, product replacement and processing action content, consistency judgment logic of multi-source information is constructed, the sequence structure is constructed according to the time field to guarantee the integrity and accuracy of record connection, the differences of each field content in the same period are identified and a collaborative identifier is generated based on the patient identity, the correlation ability of multi-party data between cross-period and cross-person is improved, and finally the image and nursing content are encapsulated according to the time sequence to form a continuous graphic view with clear structure, consistent content and comparison.

The invention discloses a night emergency intelligent doorbell reminding system for medical technical examination. An operation method of the system comprises the following steps: step 1, realizing self-adaptive diagnosis and treatment management through intelligent system integration and time scheduling; 2, realizing nurse real-time positioning and guide service optimization through a Bluetooth positioning tag; 3, intelligent navigation and information pushing in a hospital are achieved through the augmented reality technology, and the system management module is used for integrating an intelligent system and controlling the state of an examination room according to the diagnosis and treatment time period of the hospital; the positioning management module is used for tracking real-time position information of a nurse through a Bluetooth positioning tag, and the augmented reality module is used for establishing a hospital internal navigation system by using an augmented reality technology, so that the medical experience of a patient is improved; according to the invention, the quality and efficiency of hospital night emergency service can be effectively improved, the waiting time of a patient is reduced, and the satisfaction of the patient is improved.

The invention discloses an operation system for main researchers of clinical trials, which relates to the technical field of clinical trials and comprises a patient management end, a task management and reminding end, a visit plan and arrangement end, a data collection and recording end, a report generation and analysis end, an adverse event report end, a treatment management end and a communication and cooperation end. The patient management end, the task management and reminding end, the visit planning and arrangement end, the data collection and recording end, the report generation and analysis end, the adverse event report end, the treatment management end and the communication and cooperation end are in data communication through a private network and a private line network. The method has the effects of helping main researchers to effectively manage the test work and improving the quality and reliability of the test.

The invention relates to the technical field of chronic respiratory disease diagnosis and treatment, and discloses a chronic respiratory disease diagnosis and treatment management system based on artificial intelligence. The system comprises a breath data dynamic acquisition module, a pathological feature extraction module, a multi-dimensional illness state evaluation module, an abnormal focus positioning module and an individualized diagnosis and treatment strategy generation module. According to the system, breathing waveform, oxyhemoglobin saturation time sequence and lung sound feature data are collected in real time through a multi-mode sensor, key pathological features are extracted through time-frequency conjoint analysis, trend decomposition and spectrum energy distribution calculation, and then a comprehensive disease severity score is generated through a deep feature fusion network. And matching and marking potential focus positions by combining a pathological feature library, and finally dynamically adjusting the drug dosage and a rehabilitation training scheme. According to the system, intelligent management of the whole process of chronic respiratory disease diagnosis and treatment is achieved, comprehensive support is provided for diagnosis and treatment decisions by means of multi-dimensional data integration and accurate analysis, and the clinical requirement for individual management of chronic respiratory diseases is met.