120 results about "Initial treatment" patented technology

A system for administering treatment with a medical device includes a medical device capable of delivering a medical treatment to a patient. An electronic computing device has a processor, computer-readable memory, and a power supply. The electronic computing device is in communication with the medical device. A patient interface is in communication with the electronic computing device and the medical device. The electronic computing device is configured to: receive an initial electronic treatment protocol; communicate the initial electronic treatment protocol to the medical device to enable an initial treatment of the patient; receive patient input through the patient interface; receive an updated treatment protocol based on the patient input; and communicate the updated treatment protocol to the medical device to enable an updated treatment of the patient.

The invention provides a gynecological disease diagnosis and treatment method and system fused with an electronic medical record, and relates to the technical field of medical informationization, and the method comprises the steps: collecting the multi-modal diagnosis and treatment data of a patient, and constructing a personalized medical database through a self-encoding network; deploying a plurality of agents based on a dynamic causal network, and generating an initial treatment scheme in combination with deep reinforcement learning; through real-time data acquisition and a multi-objective optimization algorithm, the scheme is dynamically optimized by fusing expert decision features. According to the invention, personalized precise treatment of gynecological disease diagnosis and treatment can be realized, the treatment effect is improved, and the complication risk is reduced.

The invention discloses a doctor-patient negotiation method and device fusing LLM and a multi-agent architecture, equipment and a medium, and relates to the technical field of doctor-patient negotiation. The doctor-patient negotiation method comprises the following steps: acquiring doctor-patient background information, and constructing a doctor agent, a patient agent and a coordination agent based on a large language model. The doctor agent generates a preliminary treatment regimen. The patient agent generates feedback to the preliminary treatment regimen. The coordination agent parses the feedback, generating a structured acceptance score and a semantic vector. The dynamic belief is updated based on the semantic vector doctor agent. And performing fuzzy utility evaluation on the current treatment scheme, and judging whether strategy adjustment is triggered or not. And the coordination agent calculates the adjustment amount of each issue based on the acceptance difference value, the patient yielding willingness coefficient and the maximum yielding amplitude, and obtains a new quotation scheme. And triggering a belief calibration and strategy reconstruction process at a preset stage node of multiple rounds of negotiation to obtain a new strategy. And when the negotiation round reaches a preset maximum round number, outputting a final treatment scheme.

The invention relates to the technical field of clinical experiment data processing, and discloses a clinical experiment data analysis method based on reinforcement learning, and the method comprises the steps: obtaining time sequence physiological parameters and treatment scheme execution state parameters; performing hierarchical feature extraction on the time sequence physiological parameters, constructing a dynamic response feature model, and generating an initial treatment response evaluation model in combination with the execution state parameters; loading risk constraints and curative effect indexes to generate a comprehensive evaluation model, and simulating to obtain strategy regulation and control data; constructing and training a reinforcement learning decision model, and generating a treatment path correction model and initial treatment parameters; obtaining dynamic strategy adjustment information, and constructing a multi-stage optimization model for iterative optimization to obtain optimal treatment path parameters; reasoning a curative effect standard reaching probability based on a real-time model, and adjusting a strategy to realize dynamic curative effect matching. According to the method, the clinical data dynamic analysis and treatment scheme optimization capability is improved, and the method is suitable for precise medical scenes.

The invention provides an intensive care method and system based on intelligent analysis, and the method comprises the steps: collecting multiple physiological data, including electrocardiogram, blood pressure and the like, of a critical patient in real time through a sensor network; cleaning and standardizing the data; calculating the weight of each physiological data by using a dynamic weight evaluation formula; predicting an abnormal trend; calculating a risk score of the patient by using a comprehensive risk assessment model according to the weight and the abnormal trend; when the score exceeds a threshold value, the system automatically gives an early warning and sends information to the medical staff, and provides preliminary treatment suggestions at the same time. The method combines a traditional intensive care technology with a modern sensor network and a data processing technology, and aims to improve the treatment efficiency and level of critical patients.

The embodiment of the invention discloses a spinal metastatic tumor treatment scheme generation system. According to one specific embodiment, the system comprises a data processing server, an information fusion server and a scheme generation server which are in communication connection with one another, and the data processing server is used for preprocessing multi-source patient data to obtain standard multi-source patient data; the information fusion server is used for executing the following steps: performing feature code fusion on standard multi-source patient data to obtain a multi-source patient feature vector; performing feature enhancement on the multi-source patient feature vector to obtain a joint patient characterization vector; generating an initial therapeutic schedule result based on the joint patient characterization vector; and the scheme generation server is used for performing feature decision processing on the initial treatment scheme result to obtain a final treatment report. According to the embodiment, waste of computing resources can be reduced, and system response time can be shortened.

The invention provides a dynamic adjustment method based on a depression mind-correcting treatment scheme, and relates to the technical field of medical care information, and the method comprises the steps: collecting multi-dimensional information of a patient, and collecting life behavior risk data, psychological scale data and cognitive function evaluation data; comprehensively evaluating the depression level of the patient; determining the priority of a treatment therapy module according to the multi-dimensional information of the patient; generating an initial treatment scheme; calculating a daily task comprehensive weight value, and dynamically adjusting the training content of the next day; and evaluating the state of the patient in stages, recalculating the priority of each therapy module, and optimizing the therapeutic scheme. Through multi-dimensional data fusion evaluation and intelligent algorithm dynamic adjustment, a complete closed-loop feedback optimization system is constructed, precision and individuation of a depression treatment scheme are achieved, the treatment effect and patient compliance are effectively improved, the recurrence risk is reduced, and a more scientific and effective treatment scheme is provided for depression patients.

The invention relates to an Agent AI-based full-process intelligent radiotherapy system and a working method thereof, the system comprises a treatment Agent, a feedback Agent and a QA Agent, the feedback Agent is connected with the treatment Agent, the input of the treatment Agent is multi-modal data, and an initial radiotherapy scheme is dynamically output through deep learning and an evolutionary algorithm; the feedback Agent is connected with the multi-sensor system and used for monitoring user state data of the patient in real time, correspondingly adjusting treatment parameters according to an initial treatment scheme and outputting an optimized treatment scheme; and the QA Agent is used for monitoring key parameters in the treatment process, performing early treatment verification and later quality evaluation, and outputting a quality assurance report. Compared with the prior art, multi-Agent mutual cooperation is designed, multi-modal data are integrated, full-process automation from treatment scheme determination, data acquisition, target region sketching, plan generation, treatment execution to QA is achieved, dependence on manual intervention can be reduced, and treatment individuation and efficiency are improved.

The invention discloses a tumor postoperative treatment staged planning method based on artificial intelligence. The method comprises the following steps: S1, constructing a multi-modal medical data set; s2, performing standardization processing on the acquired multi-modal medical data set to form a standardized data set which can be used for feature extraction; s3, generating a unified patient feature vector; s4, according to the characteristics of tumor postoperative treatment, dividing the whole treatment process into a postoperative immediate recovery stage, a postoperative recovery middle stage and a long-term follow-up visit stage, and defining a corresponding optimization target for each stage; s5, based on the patient feature vector and the optimization target of each stage, generating an initial treatment plan by using a deep ant colony algorithm; and S6, outputting a staged treatment scheme. According to the method, the professional and technical thresholds required by traditional modeling are reduced, and the universality and convenience of three-dimensional modeling are improved.

The invention provides an emergency pre-examination and sorting system which comprises an information registration module used for registering basic information and medical history symptom information of a patient; the pre-evaluation module is used for establishing a symptom data set according to the basic information of the patient and the medical history symptom information, establishing a total data set according to the symptom data set and related triage rules in medical data literature, performing classifier training according to the total data set, performing triage category probability analysis by using a naive Bayesian algorithm according to the condition of the patient, and obtaining a triage classification probability result; a preliminary treatment examination department and a doctor are recommended; the grading module is used for grading the patients according to the critical degrees of the illness states according to the pre-evaluation result; the post-processing module is used for filing and storing the doctor-seeing record of the patient, the preliminary treatment examination department and doctor and the grading information, the disease data set of the patient is automatically analyzed through an algorithm, the preliminary treatment department and doctor are quickly recommended, the patient is prevented from being mistakenly guided to an improper department, and unnecessary examination and treatment are reduced.

A machine learning-assisted intelligent device for optimizing personalized cancer treatment based on genomic data, the device comprising the following: a genome data input unit configured to receive and preprocess genome sequences from a variety of external data sources, the preprocessing including noise reduction, sequence alignment, and filtering of irrelevant genome segments; a mutation detection unit comprising a deep learning-based processing module, wherein the mutation detection unit is configured to compare the preprocessed genome sequences with a database of known cancer-related mutations and biomarkers and to create a mutation profile associated with a patient's cancer; an optimization unit for machine learning models comprising at least one neural network architecture, wherein the optimization unit is configured to receive the mutation profile, analyze the identified mutations, correlate the mutations with historical patient outcomes, and generate an initial treatment recommendation; a treatment recommendation engine configured to use reinforcement learning algorithms, wherein the engine continuously learns from real-time patient responses to previous treatments and dynamically adapts treatment strategies based on updated genomic data and evolving patient conditions, thus providing an optimized treatment plan; an outcome prediction module configured to analyze potential outcomes of the recommended treatments based on predictive analysis models, whereby the module generates a probability value for treatment success and presents a detailed explanation of the correlation between genomic markers and the expected efficacy of the treatment; a secure data transmission interface configured for bidirectional communication with hospital networks and genome research centers, with the interface complying with data protection standards to protect sensitive patient information; a display interface configured to visually represent the results of genomic analyses, treatment recommendations, and outcome predictions, wherein the display interface allows user interaction to adjust treatment parameters based on clinical inputs; and a power management unit configured to regulate energy consumption, wherein the power management unit includes a cooling system to maintain the operating temperature of the device during high-performance data processing tasks.

The invention provides an application of a T lymphatic activation related cytokine as a biomarker in prediction of children immune globulin non-reactive Kawasaki disease. The team finds that in patients of an IVIG sensitive group and an IVIG non-response group, differences of expression levels of IL-6 and IL-17 before and after treatment have statistical significance; meanwhile, ROC curve analysis shows that IL-6 and IL-17 serve as early warning signals, and the prediction efficiency of the IVIG-unreacted Kawasaki disease is remarkably superior to that of existing prediction factors. Particularly, the levels of IL-6 and IL-17 are re-evaluated after initial treatment, so that the early prediction accuracy of the IVIG unresponsive Kawasaki disease can be further improved. By introducing IL-6 and IL-17 as novel biomarkers, early accurate prediction of the IVIG unresponsive Kawasaki disease is realized. Compared with the prior art, the method can provide a quicker and more accurate risk assessment basis for clinicians, so that early recognition of high-risk patients, optimization of subsequent treatment schemes and reduction of serious complications are facilitated, and a new thought and direction are provided for clinical diagnosis and treatment.

The present invention provides a full-automatic tremella pedicle removal, harvesting and waste separation and processing system, comprising a feeding mechanism, a conveying and cutting mechanism, a harvesting mechanism and a mushroom stick processing mechanism, the harvesting mechanism is used for collecting the cut tremella, and the mushroom stick processing mechanism processes the mushroom sticks; the feeding mechanism moves the mushroom sticks with tremella in the material frame to the processing position of the conveying and cutting mechanism, and realizes the stacking of the empty material frame, the harvesting mechanism lifts the ear pieces around the tremella upward to a certain height, and the ear pedicle in the middle of the tremella is completely exposed, the conveying and cutting mechanism cuts off the ear pedicle of the tremella to collect the harvested tremella, and then transports the harvested mushroom sticks to the mushroom stick processing mechanism, and the mushroom stick processing mechanism separates the plastic film and the culture medium in the mushroom sticks. The present application realizes the steps of automatic feeding, empty frame stacking, ear pedicle removal and harvesting, finished tremella collection and preliminary processing of waste mushroom sticks, has a high degree of automation, and is suitable for large-scale promotion and use.

The invention relates to the technical field of oral medical treatment, in particular to a tooth orthodontic treatment scheme planning system, which comprises a database module, a processing module and a planning module, the data acquisition module is used for acquiring initial oral data of a patient before treatment and stage monitoring data in a treatment process; the scheme generation module is used for screening out a complete treatment scheme with the highest similarity in the database through feature similarity matching and generating an initial treatment scheme; the risk assessment module is used for extracting risk factors such as periodontal support force and calculating a risk level; the dynamic adjustment module is used for setting a tooth movement distance deviation threshold value according to the risk level, and comparing an actual tooth movement distance deviation value to generate an adjustment treatment scheme; and the doctor rechecking module is used for the doctor to adjust and recheck the initial treatment scheme and the adjusted treatment scheme according to the individual parameters of the patient. According to the scheme, intelligent planning, dynamic adjustment and scientific review of an orthodontic scheme can be realized, and the treatment accuracy and safety are improved.

The invention relates to the technical field of medical artificial intelligence, and discloses a non-small cell lung cancer immunotherapy risk assessment method and system and a storage medium, and the method comprises the steps: constructing an optimal strategy tree model capable of dividing a patient into a plurality of subgroups based on a historical patient data set, and determining an initial optimal treatment strategy for each subgroup; determining a subgroup to which a new patient belongs and an initial treatment strategy thereof according to the model; in the treatment process, the deviation degree between the individual response trajectory of the patient and the average response trajectory of the subgroup to which the individual response trajectory belongs is calculated; and when the deviation degree exceeds a preset threshold value of the subgroup, triggering an adaptive adjustment mechanism, and outputting an updated treatment suggestion. By establishing a dynamic monitoring and closed-loop feedback mechanism based on the subgroup benchmark, the technical problem that an existing scheme is difficult to carry out prospective identification and dynamic intervention on individualized risks is solved, so that the accuracy, safety and individualized level of non-small cell lung cancer immunotherapy are improved.

The invention provides radiotherapy equipment for angle adjustment between treatment fractions during multi-fraction radiotherapy. The radiotherapy equipment comprises an angle selection unit, an angle adjustment unit and an angle adjustment unit, wherein the angle selection unit is used for executing irradiation angle selection of initial treatment fractions; an angle adjustment unit for performing angle adjustment in a subsequent treatment fraction based on the irradiation angle of the initial treatment fraction; and the monitoring and adjusting unit is used for executing dose accumulation, monitoring and adjustment on the basis of the irradiation angle of the initial treatment fraction and the adjusted angle in the subsequent treatment fraction.

The invention relates to the technical field of medical treatment, in particular to a deformation registration method and system, a self-adaptive treatment planning method and a treatment planning system which are used for improving the accuracy of image deformation registration, and the method comprises the steps: obtaining a plan image, a fractional image and dose distribution data corresponding to an initial treatment plan of a patient; inputting the plan image, the graded image and the dose distribution data corresponding to the initial treatment plan of the patient into a trained deformation registration model, performing deformation registration on the graded image and the plan image, and outputting a deformation field; wherein the trained deformation registration model is obtained based on dose distribution consistency loss training between dose distribution data corresponding to the initial treatment plan and deformation dose distribution data corresponding to the deformation field.

A method of treating psoriatic arthritis in a patient by administering an IL-23 specific antibody, e.g., guselkumab, in a clinically proven safe and clinically proven effective amount and the patient achieves significant ACR20 / 50 / 70, PASI70 / 90 / 100, MDA, HAQ-DI, SF-36 PCS, MCS, LEI / dactylitis, PASDAS, GRACE, mCPDAI, DAPSA or RAPID3 improvement as measured 16, 24, 32, 40 and 48 weeks after initial treatment.

Disclosed herein are methods of treating psoriasis and other IL-17-dependent conditions with an anti-interleukin 17A / F nanobody for approximately 24 weeks, followed by withdrawal of treatment in responding patients with the anti-interleukin 17A / F nanobody for a period of at least 4-20 weeks. Disease modification may be achieved by no later than week 24 with the anti-interleukin 17A / F nanobody such that responders may demonstrate sustained normalization of peripheral and / or cutaneous biomarkers such as IL-17A, IL-17F, and / or IL-22. Treatment methods as contemplated herein which have been paused may be re-started based on the subject's condition. Treatment beyond 24 weeks also achieves unexpectedly high efficacy in responders who have not quite reached full skin clearance in the initial treatment period.

The invention provides a simulation evaluation method based on focused ultrasound and electronic equipment, and relates to the technical field of computers. The method comprises the following steps: generating a three-dimensional part model and initial treatment parameters corresponding to a target part according to medical image data of the target part; based on the three-dimensional part model and the initial treatment parameters, transmitting a simulation ultrasonic pulse to a three-dimensional focus model corresponding to the target tissue in the three-dimensional part model; according to the method, the acoustic parameters and the thermal parameters of the preset sampling points in the three-dimensional part model are obtained, the evaluation item for the target tissue is calculated according to the acoustic parameters and the thermal parameters, and the evaluation result is generated according to the evaluation item, so that the three-dimensional part model can be constructed by considering the acoustic characteristics and the thermal characteristics corresponding to the target part, and the evaluation result is generated according to the three-dimensional part model. If the evaluation result indicates that the treatment effect corresponding to the simulation treatment operation is poor, the training medical staff can adjust the treatment scheme so as to optimize the treatment effect, summarize the treatment experience and improve the training effect.

Optimized bio-synchronous drug delivery begins with establishing a bio-synchronous treatment protocol that incorporates individual temporal and innate biological characteristics into a pharmacological treatment plan. The bio-synchronous treatment protocol is thereafter initiated using bioactive agent delivery device. Bio-synchronous drug delivery includes continual collection of patient data such as physical, psychological, temporal and environmental characteristics. This data is analyzed so to not only determine an initial treatment protocol but to also determining whether modification to the ongoing bio-synchronous treatment protocol is required. And, responsive to determining a modification is required the system modifies the bio-synchronous treatment protocol and use of delivery device. These modifications and treatment protocols can include reactive and proactive psychological support supplied to the patient in a variety of formats.

The invention discloses a nerve regulation and control treatment method, system and device and a medium, and the method comprises the steps: designing a nerve regulation and control investigation and inquiry template, evaluating the nerve state of a patient, and generating an evaluation report; carrying out sound treatment technology applicability screening on the patient; selecting a plurality of sections of universal biological natural sound noise, providing the universal biological natural sound noise to the patient passing the applicability screening of the sound treatment technology for audition, and selecting the universal biological natural sound noise with a relatively high adaptability threshold as an initial nerve regulation treatment audio; carrying out hearing test, generating debugging parameters, debugging the initial treatment audio, and generating recommended nerve regulation treatment audio; and performing nerve regulation treatment on the patient based on the recommended nerve regulation treatment audio, and checking the treatment effect. According to the invention, a series of hearing tests are carried out on the patient, the debugged recommended nerve regulation treatment audio is generated for patients with different symptom types, and the nerve regulation treatment effect is effectively improved.

The disclosed principles provide a system and method for improving brain health in a virtual reality environment. The system includes a virtual reality appliance and an artificial intelligence enabled program for providing and customizing the virtual reality environment with a treatment plan. The artificial intelligence enabled program includes an initial treatment phase wherein a user's baseline metrics are measured. Using these metrics, a treatment plan is created during a treatment plan development phase. The treatment plan is implemented during a treatment phase through a series of repeated mindfulness, cognitive, and physical exercises presented in a virtual reality environment. Data corresponding to the user's inputs during treatment is collected and stored. An artificial intelligence program analyzes user input data and modifies the treatment plan accordingly to optimize treatment. Treatment and evaluation and modification are alternately repeated according to the personalized, artificial intelligence-modified treatment plan to strengthen neural pathways.

The present disclosure relates to methods of electroconvulsive therapy (ECT) for a patient's brain based on determining an optimal individualized current amplitude for a patient by (1) dividing an optimal E-field strength (optimal Ebrain) by a baseline E-field strength (baseline Ebrain) of the patient's brain, or (2) performing an initial treatment to determine a patient's amplitude titrated seizure threshold (STa), followed by use of a multiplier value multiplied by the STa for an individualized amplitude for subsequent treatments. Methods of ECT using optimal individualized current amplitude provide an antidepressant effect and reduce adverse cognitive effects on the patient's brain.

This invention discloses a method for predicting the dynamic conductivity of biological tissues considering the pulse dispersion effect. The method includes: constructing a two-dimensional dual-needle electrode geometric finite element model, setting boundary conditions and initial treatment parameters; introducing a Debye function into the finite element model to characterize the change of tissue dielectric constant with frequency; performing frequency domain analysis on the applied pulse signal and converting the Debye function from the frequency domain to the time domain, allowing the polarization vector to couple with the electric field to participate in transient solutions, thereby obtaining a voltage and current dataset including the effect of pulse dispersion; constructing a tissue dynamic conductivity prediction model and training the prediction model using the voltage and current dataset; inputting the voltage and current response data of the tissue to be determined into the trained model to obtain the tissue dynamic conductivity prediction result. This invention can improve the consistency between the finite element current calculation results and the actual tissue electrical response, and improve the accuracy of tissue dynamic conductivity prediction. It is applicable to dynamic conductivity prediction in electroporation therapy, providing a reference for electroporation therapy.

The present invention provides a system and a method for non-face-to-face monitoring of a health condition. The method is a method for non-face-to-face monitoring of the health condition of a subject, performed by a server, and may comprise the steps of: when a monitoring service for a health condition is requested from a user terminal through a dedicated application, generating reservation management information in response to a service selection signal received from the user terminal; and firstly performing AI diagnosis by using treatment information and consultation information received from a service-linked terminal on the basis of the reservation management information, and generating result data of treatment and consultation on the health condition of a subject on the basis of the result of the AI diagnosis, wherein the step of generating the result data comprises the steps of: when the monitoring service for the health condition of the subject corresponds to an initial treatment, generating non-face-to-face consultation information on the health condition of the subject; when the monitoring service for the health condition of the subject corresponds to a subsequent treatment, generating non-face-to-face treatment information on the health condition of the subject; and generating, as result data, a result determined in response to the non-face-to-face treatment information and the non-face-to-face consultation information on the basis of standard data.

The present disclosure relates to a dental arch arrangement method, device, equipment and storage medium. An initial treatment dental arch model of a target user is obtained, wherein the initial treatment dental arch model is a dental arch model obtained after single jaw arrangement of the oral cavity of the target user; for each tooth on the upper jaw or the lower jaw of the initial treatment dental arch model, a transformation matrix of each tooth relative to the corresponding initial dental arch is determined; the transformation matrix corresponding to each tooth is kept unchanged, and each tooth is controlled to be arranged on the dental arch to form a target treatment dental arch model containing a target dental arch, wherein the target treatment dental arch model is a dental arch model whose occlusal relationship of the upper jaw and the lower jaw meets a preset treatment standard. Therefore, the transformation matrix of each tooth on the initial treatment dental arch model relative to the corresponding initial dental arch is kept unchanged, and each tooth is arranged on the corresponding dental arch, so that the occlusal relationship of the upper jaw and the lower jaw is adjusted to the preset treatment standard, and finally a dental arch model meeting the preset treatment standard is obtained.

The application discloses a medicine patch with gradient effect on human body, which comprises, from outside to inside, a back layer, a heating layer and a solid medicine layer, wherein the solid medicine layer is provided with solid medicine A; and further comprises a medicine liquid cavity for sealing liquid medicine B; when used, the medicine patch is attached to the human body for a set time, the medicine liquid cavity can be opened and the liquid medicine B can flow into the solid medicine layer; the solid medicine A can preliminarily treat related diseases under the action of heating, and the liquid medicine B is added in a progressive manner after the set time; the medicine patch has the gradient treatment requirement and the treatment effect, and can further drive the residual effect of the solid medicine B to continuously act on the affected area, improve the utilization rate of the medicine, and make the treatment medicine more targeted; thus, the traditional inertial thinking of the medicine patch is changed, interval medicine for treatment is made possible, the medicine effect is improved, and the foundation for the final treatment effect is laid.

The invention provides a radiotherapy system and a storage medium, and relates to the technical field of medical treatment, in particular to the technical field of radiotherapy. According to the specific implementation scheme, a first guide image and a first plan image are obtained, and then a first image deviation value is determined according to the first guide image and the first plan image; and finally, adjusting the initial treatment plan based on the first image deviation value to generate a target treatment plan. According to the method, the rotation angle between the tumor position of the patient and the tumor position in the positioning image can be eliminated under the condition that treatment is not interrupted.

Examples disclosed herein provide computer-implemented methods and apparatus of determining a treatment for treating a subject's skin or hair. Such a method comprises: receiving, as input, dermatological data indicative dermatological data indicative of the subject's skin or hair following treatment by an initial treatment, the subject's skin or hair having an associated health condition; processing the dermatological data using an condition determination machine learning model to determine an updated health condition of the subject's skin or hair; determining a modified treatment for treating the updated health condition of the subject's skin or hair in dependence on the determined updated health condition of the subject's skin or hair; and providing, as output, the determined modified treatment.