1137 results about "In patient" patented technology

A fluid management system for use in a tissue resection procedure includes a controller. An inflow pump is operated by the controller and configured to provide fluid inflow through a flow path to a site in patient's body. An outflow pump is operated by the controller and configured to provide fluid outflow through a flow path from the site in patient's body. A motor driven resecting device may be provided for resecting tissue at the site. The controller is configured to actuate an inflow pump and an outflow pump in response to various signals and various algorithms are provided to provide malfunction warnings and assure safe operation.

This specification describes systems and methods for performing endoscopy, obtaining medical images for inflammatory bowel disease (IBD) and scoring severity of IBD in patients. The methods and systems are configured for using machine learning to determine measurements of various characteristics related to IBD. The methods and systems may also obtain and incorporate electronic health data of patients along with endoscopic data to use for scoring purposes.

The present disclosure provides methods for the acute treatment of migraine with or without aura, comprising the administration of ubrogepant. In particular, the present disclosure provides methods for the acute treatment of migraine in patients having hepatic impairment; in patients with renal impairment; and in patients concurrently taking CYP3A4 modulators or BCRP and / or P-gp only inhibitors.

The invention provides a virtual reality rehabilitation training self-adaptive regulation and control method and system based on a heart flow double-mapping model, and the method comprises the steps: constructing the heart flow double-mapping model in advance, which comprises a patient data and heart flow state input mapping model and a task parameter and heart flow state output mapping model; collecting multi-dimensional data of the patient in virtual reality rehabilitation training in real time; the current cardiac flow state is calculated through the patient data and cardiac flow state input mapping model, if the current cardiac flow state does not reach the target cardiac flow state, the optimal task parameter combination is solved through the task parameter and cardiac flow state output mapping model under the medical rule constraint condition, virtual reality training task parameters are dynamically adjusted, and the target cardiac flow state is obtained. The heart flow state of the patient reaches the preset target. According to the method, through multi-dimensional data fusion and cardiac flow double-mapping model collaborative optimization, a high cardiac flow state of a patient can be accurately induced and maintained, and the participation degree and the curative effect of rehabilitation training are remarkably improved.

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 belongs to the technical field of stomatology, and particularly relates to an upper jaw fixing expansion appliance which comprises a spiral expansion device, a plastic base, a connecting rod, a retention device and a dental retraction traction hook. The spiral expander is positioned in the center of the appliance, and the plastic base plate is two parts which are separated from each other in the center and connected with the spiral expander and covers the hard palate part of the upper jaw. The retention device is composed of a milk molar or premolar casting continuous belt ring and a first molar independent casting belt ring. And the left and right dental retraction traction hooks are positioned in the plastic base and are used for retracting and pressing the first molar of the upper jaw of buccal inclination after the expansion of the arch. The appliance disclosed by the invention is wide in clinical application range, and is suitable for light and moderate teenager patients with lateral maxillary development insufficiency and maxillary posterior tooth buccal inclination compensation. According to the invention, a good bony expansion effect can be realized for patients in a replacement dentition stage or a permanent dentition early stage and patients in rapid maxillary expansion, and excessive buccal inclination and movement of teeth are reduced.

The invention discloses a lung squamous cell carcinoma survival probability prediction system fusing multiple models, and relates to the technical field of medical data analysis. Comprising a data acquisition module used for acquiring a lung squamous carcinoma clinical data set and an inspection index of a patient; the data preprocessing and dynamic feature table construction module is used for preprocessing the lung squamous cell carcinoma clinical data set in existing data processing and dynamically updating a physiological feature information table; the model training and predicting module is used for carrying out training and online prediction on various survival analysis models; and the SHAP interpretation and weight calculation module is used for calling a corresponding SHAP algorithm to obtain an average absolute SHAP value of each input feature. According to the method, model interpretation conflict measurement, invalid variable elimination and pseudo high risk verification are provided, and automatic arbitration or artificial recheck is realized through weighted scoring, so that the reasonability and safety of prediction and intervention suggestions are ensured, the decision risk is reduced, and the clinical trust is enhanced.

The invention provides a patient state auxiliary judgment and posture adjustment method, device and system, and relates to the technical field of medical equipment. The method comprises the following steps: acquiring real-time state data of a patient; generating a three-dimensional posture model and emotion parameters of the current body posture of the patient based on the real-time state data; according to the difference degree of the preset target posture and the three-dimensional posture model, a posture adjustment instruction is generated in combination with a manual adjustment instruction of a doctor; and based on the posture adjustment instruction, prompting the patient to adjust the posture until the difference degree is smaller than a preset threshold value and the emotion parameters are in a target emotion range and lasts for a preset duration, and confirming that the patient completes examination preparation. Through the technical scheme provided by the invention, the problems that accurate state judgment is difficult to obtain and posture auxiliary adjustment cannot be performed on the patient before the patient is examined are solved, the accuracy of state perception of the patient and the efficiency of posture adjustment are improved, and the examination experience of the patient is improved.

The present disclosure provides methods for the acute treatment of migraine with or without aura, comprising the administration of ubrogepant. In particular, the present disclosure provides methods for the acute treatment of migraine in patients having hepatic impairment; in patients with renal impairment; and in patients concurrently taking CYP3A4 modulators or BCRP and / or P-gp only inhibitors.

The invention relates to the technical field of sleep medical diagnosis, and discloses a method for diagnosing obstructive sleep apnea of a patient. The method comprises the steps that nasal pressure airflow, thoracico-abdominal breathing effort and blood oxygen saturation waveform of all-night sleep are obtained, and standardized signal flow is generated through quality evaluation and compensation. And executing sleep stage perception respiratory event analysis, and outputting an event sequence with a time sequence and a type label. And inputting the sequence into an apnea association network for event chain mining and mode extraction, and generating an event association graph and a key pathological feature vector. And performing severity grading of sleep structure dependence, outputting severity indexes of sleep stages, and finally deducing a personalized treatment path. According to the method, the accuracy of event interpretation is improved by sensing the sleep stages, the dynamic mode between the events is mined by using the association network, and more refined diagnosis is realized.

The present disclosure provides methods for the acute treatment of migraine with or without aura, comprising the administration of ubrogepant. In particular, the present disclosure provides methods for the acute treatment of migraine in patients having hepatic impairment; in patients with renal impairment; and in patients concurrently taking CYP3A4 modulators or BCRP and / or P-gp only inhibitors.

An automated adaptive radiotherapy system based on machine learning for designing and adapting personalized dosing plans and a corresponding system, the system comprising: • a data acquisition module to collect multimodal patient data such as anatomical images, genomics, physiological signals and electronic health records; • a preprocessing department that performs the normalization, alignment, segmentation and transformation of the acquired data into data structures suitable for predictive modeling; • a dose prediction engine containing at least one machine learning model trained to predict personalized three-dimensional radiotherapy dose distributions and dose-volume histograms from the preprocessed data; • an adaptation module to receive updated clinical data and automatically adapt the dosing schedule to intra-fraction and inter-fraction changes in patient anatomy and response to treatment; • a clinician dashboard that displays predicted dosing schedules, allows clinician interaction, and can make the model interpretable through explainable AI; • a data security and compliance layer that protects data through encryption, access control, and regulatory compliance.

The invention provides a motion rehabilitation method, device and equipment for movement fear of a cardiovascular disease combined weak patient. The method comprises the following steps: S101, establishing different potential category influence factor models of movement fear of the cardiovascular disease combined weak patient on the basis of a potential category analysis method; s102, based on a knowledge graph technology, aggregating related evidence-based evidences of health education and exercise rehabilitation of the movement fear of the senile cardiovascular disease and weak patient, and constructing to obtain a knowledge graph-based exercise rehabilitation knowledge base of the movement fear of the senile cardiovascular disease and weak patient; s103, in combination with the potential category influence factor model and the multi-modal data of the patient, constructing a multi-modal data-based digital twinborn body of the senile cardiovascular disease combined with the dynamic terrorism of the weak patient; and S104, according to the dynamically updated digital twinborn model, performing matching from the exercise rehabilitation knowledge base according to the health target, the body condition, the real-time environment and the preference characteristics of the patient to obtain personalized health education and exercise prescription recommendation.

The invention relates to the technical field of medical treatment, and discloses a patient cognitive impairment recognition method and system and electronic device.The method comprises the steps that patient original data are obtained, and the patient original data comprise clinical biochemical data, image data and cognitive behavior data; preprocessing the original data of the patient to obtain preprocessed data; feature extraction is conducted on the preprocessed data, key features are obtained, and the key features comprise clinical biochemical features, image features and cognitive behavior features; fusing the clinical biochemical features, the image features and the cognitive behavior features to obtain fused features; and determining a cognitive impairment recognition result based on the fusion features and the cognitive impairment recognition function. According to the embodiment of the invention, the early detection rate of cognitive impairment of the pituitary adenoma patient is improved, missed diagnosis and misdiagnosis are reduced, and the early warning cognitive risk when obvious clinical symptoms do not appear in cognitive impairment recognition of the pituitary adenoma patient is reduced.

The invention discloses a chronic obstructive pulmonary disease patient screening system for the respiratory medicine department, particularly relates to the field of computer-aided diagnosis, and is used for solving the technical problems that an existing screening method is low in screening efficiency, low in patient adaptability and difficult to popularize on a large scale in a basic level. According to the system, a standardized patient medical event sequence is constructed by obtaining a target population medical record containing medicine distribution and disease diagnosis codes; identifying a characteristic medication and diagnosis mode before definite diagnosis of the chronic obstructive pulmonary disease based on a sequence pattern mining technology; constructing a medical knowledge graph by using the modes, obtaining a feature embedding vector representing a chronic obstructive pulmonary disease medical trajectory through graph neural network learning, and establishing a high-risk digital portrait; inputting the medical sequence of the person to be screened into a feature extraction model based on same map training, and generating an individualized risk probability prediction value by calculating the matching degree of the medical sequence and the digital portrait; and a screening result report is automatically generated, so that efficient and noninvasive early risk screening is realized.

The invention discloses a brain small vascular disease lower limb dysfunction self-adaptive electrical stimulation auxiliary rehabilitation system in the technical field of medical instruments, and the system comprises a data collection module which is used for obtaining the multi-modal data of a patient in real time; the decision regulation and control module is used for generating dynamically optimized electrical stimulation parameters and rehabilitation task instructions based on a deep reinforcement learning algorithm and patient individualized pathological characteristics according to the multi-modal data; the electrical stimulation execution module is used for synchronously regulating and stimulating nerve targets according to the optimized electrical stimulation parameters; and the interactive virtual reality module is used for combining immersive gait training and cognitive training. By detecting the multi-modal physiological data of the patient, combining the deep reinforcement learning model to dynamically optimize the electrical stimulation parameters, and coupling VR exercise training and cognitive training, the three-in-one collaborative rehabilitation mode of electrical stimulation-physical treatment-cognitive intervention is realized, the rehabilitation training efficiency is improved, the relapse risk of the patient is reduced, and the rehabilitation training experience of the patient is enhanced.

The invention discloses an esophageal cancer prognosis risk analysis method and system based on machine learning, and a medium, and relates to the technical field of artificial intelligence technology and bioinformatics, and the method comprises the steps: 1, collecting multi-modal data of a patient, and carrying out the standardization processing, so as to construct a stable feature set; 2, constructing a plurality of machine learning models, realizing high and low risk group prediction of each machine learning model based on stable feature set modeling, and determining the machine learning model and an optimal feature set according to the high and low risk group prediction; and step 3, calculating SHAP interaction values among the features in the optimal feature set, drawing an interaction value curve according to the SHAP interaction values to obtain TopA interaction feature pairs, taking the interaction feature pairs as newly constructed features to be included in the original feature set in the step 1, and repeating the feature screening process in the step 1 and the step 2 to obtain an optimal machine learning model. Predicting high and low risk groups of patients; according to the prognosis risk analysis method, the detection specificity of high and low risk groups of local advanced esophageal cancer patients is greatly improved.

The invention provides a wound reduction screw and an implantation method thereof. The screw includes a headless screw having a narrow thread at a proximal end and a reduction cap. The cap is adapted to be coupled to the headless screw via the narrow threads after the screw has been inserted into a substrate, such as a patient's bone. The method involves inserting a headless screw into a bone borehole using a headless screwdriver, and coupling a reduction cap to the inserted screw using a reduction screwdriver loaded with the reduction cap. This reverse torque approach enables efficient implantation of the reduction wound screw. These innovations provide potential improvements to patient care, particularly in terms of bone reposition traction and fixation.

The invention discloses an olfactory reconstruction electrical stimulation regulation and control system for a nerve prosthesis, and the system comprises a sensor, an electrode array, a control unit, a signal processing module, a wireless transmission module, an electrode driving module, and a feedback collection module. The olfactory bulb, the olfactory epithelium or the olfactory cortex are electrically stimulated through the array electrode, and the smell sensing process is simulated. According to the invention, olfaction signal transmission is reconstructed by accurately regulating and controlling electrical stimulation parameters, and a patient with olfaction loss is helped to recover perception of surrounding environment smell. The system has the advantages of high precision, controllability, personalized adaptation and the like, and an innovative technical scheme is provided for perception recovery of olfactory deficiency patients.

The invention provides a postoperative cognitive impairment prediction system and method for gastrointestinal tumor surgery patients, and belongs to the technical field of postoperative cognitive impairment prediction of patients based on machine learning. The system comprises a data receiving and obtaining module, an abdomen CT feature extraction module, a patient clinical and information data coding module and a gastrointestinal tumor patient postoperative cognitive impairment prediction module. The data receiving and obtaining module extracts three-dimensional features of the abdomen image data to obtain an abdomen CT image fusion feature map; the patient clinical and information data coding module performs feature coding on the patient clinical data and the information data to obtain clinical feature vectors; and the gastrointestinal tumor patient postoperative cognitive impairment prediction module takes the abdominal CT image fusion feature map and the clinical feature vector as input and outputs a quantitative evaluation result of the postoperative cognitive impairment of the patient. According to the method, effective classification of cognitive impairment is realized, and powerful auxiliary support is provided for clinical intervention and management of postoperative patients.

The invention relates to the technical field of medical emotion early warning, and discloses an early warning system used based on a hospital platform. The system comprises a data acquisition module which is used for acquiring a patient identifier and treatment time, and acquiring voice dialogue and text record content and associated information to generate a patient data set; the sentiment analysis module is used for analyzing semantic and acoustic features of the voice and text contents and generating a sentiment analysis result set; the grading processing module is used for carrying out hierarchical division on emotions and generating a patient emotion grading result set; the information synchronization module is used for synchronizing the grading labels and the patient identifiers to a hospital information system display terminal according to specifications and generating grading information synchronization records; the intervention execution module is used for matching an AI automatic pacifying or manual intervention strategy for the patients higher than the basic warning level, and generating an intervention execution record set; and the early warning triggering module is used for marking the patient with the emotion activation risk and generating an early warning triggering result. The system can sense emotion changes of a patient in real time, active intervention is achieved, and the diagnosis and treatment order is maintained.

The invention discloses a transfer information management system in a patient hospital. The transfer information management system comprises a patient information management module, a transfer evaluation and grading module, a transfer plan generation module, an Internet of Things real-time monitoring module, a multi-department cooperation module and a quality control management module. The invention belongs to the technical field of medical informatization, and particularly provides an in-hospital transfer information management system for patients, which realizes transfer information linkage sharing and transfer quality control management through digital and intelligent means and ensures the safety of the patients.

Photoacoustic medical-device navigation systems and methods provide alternatives to those incorporating fluoroscopy for medical-device navigation in patient bodies. A medical-device navigation system can include an optical-fiber stylet, ultrasound transducers, and a console. The stylet can transmit light to an instant location of a distal tip of an elongate medical device in a patient's body and, thereby, irradiate endogenous chromophores to generate ultrasound-frequency photoacoustic pressure waves therefrom. The ultrasound transducers can detect ultrasound signals corresponding to the photoacoustic pressure waves. The console can instantiate medical-device navigation processes for navigating the elongate medical device via the stylet as the elongate medical device is advanced to the target location in the patient's body. The medical-device navigation processes can include acquiring ultrasound-signal data from the ultrasound transducers, reconstructing images from the ultrasound-signal data, and displaying reconstructed images on a display for navigating the elongate medical device to the target location in the patient's body.

A system and associated method for manipulating tissues and anatomical or other structures in medical applications for the purpose of treating diseases or disorders or other purposes. In one aspect, the system includes a delivery device including a flexible portion that is suited to access target anatomy. The flexibility of an elongate portion of the delivery device can be varied. Additionally, the delivery device can include structure that maintains the positioning of the delivery device in patient anatomy.

The present invention relates to an AI-based system and method for generating enhanced radiology reports. The system comprises a database for storing multimodal patient data, a natural language processing (NLP) module for extracting clinical information, and a machine learning module for correlating the clinical information with radiology images to identify diagnostic insights. An AI-based report generation module analyzes the images and clinical information to generate a preliminary report, which is refined based on radiologist input. The generated report is then integrated into the patient's electronic health record. The system employs techniques such as multimodal deep learning, active learning, explainable AI, and federated learning to enhance diagnostic accuracy, capture expert feedback, provide transparency, and enable multi-institutional collaboration. The invention aims to improve the accuracy, efficiency, and value of radiology reporting in patient care.

The invention belongs to the technical field of medical instruments. The invention discloses a drug coating balloon catheter and a preparation method thereof. In one aspect, a drug coated balloon catheter includes a catheter with a balloon; a drug coating at least comprising an inner coating and an outer coating is arranged on the outer wall of the balloon, and the inner coating and the outer coating are provided with drug active ingredients and different carriers respectively; when the balloon is expanded, the inner coating and the outer coating are separated from the balloon through the state change of the temperature-sensitive carrier of the inner coating under the body temperature environment of a patient and the hydration effect, and the outer coating is used for promoting corresponding active pharmaceutical ingredients to be transferred into target tissues through the carrier of the outer coating when the outer coating is separated from the balloon. On the other hand, the invention provides a preparation method of the drug coating balloon catheter. The preparation method has the advantages that the adhesiveness of the drug coating on the balloon can be effectively improved so as to reduce the delivery loss, and the release rate of the drug coating on diseased tissues can be improved so as to improve the drug transfer capacity.

This disclosure is directed to systems and techniques for detecting change in patient health based upon peak and non-peak patient activity data. In some examples, the peak and non-peak patient activity data correspond to one or more peak (time) periods and the one or more non-peak periods, respectively, where at least one peak period and at least one non-peak period corresponds a highest activity level and a lowest activity level, respectively, for a single day. If a change in patient health is detected, the techniques described herein may direct a medical device to generate for display output indicating the detection of the change in patient health.

The invention relates to a gouty arthritis patient pain management method and system based on an MDT management mode, and the method comprises the steps: automatically collecting the multivariate clinical data of a patient through integrating an existing information system of a hospital, carrying out the cleaning, standardization and structural processing through a special data preprocessing module, and carrying out the cleaning, standardization and structural processing. A machine learning prediction model trained by historical data is utilized to automatically generate a personalized MDT nursing plan, tasks are intelligently distributed to corresponding team members by means of a workflow engine, the execution condition is continuously monitored in the intervention process, and the nursing scheme is dynamically adjusted based on clinical data and prediction results which are periodically updated. And a complete'monitoring-prediction-intervention-reevaluation 'closed-loop management process is formed. The problems that a traditional MDT mode depends on manpower, efficiency is low, and decision-making lacks data support are effectively solved, and the accuracy, the collaboration and the continuity of pain management and wound surface nursing of the gouty calculus combined infection patient are improved.

The invention relates to the technical field of biological and medical diagnosis, in particular to a biomarker for predicting whether a patient suffering from pyotoxic myocardial injury has a short-term death risk or not and application of the biomarker, and the biomarker is the ratio of erythrocyte distribution width to albumin. According to the method, retrospective queue research design is adopted, two data sets, namely MIMIC-IV and eICU-CRD, are used, suppurative myocardial injury patients meeting conditions are included, covariants such as baseline features, laboratory inspection results and complication information of the patients are collected, the patients are divided into two groups according to RAR medians, the relation between RAR and short-term death of the patients is analyzed by adopting multiple statistical methods, and the accuracy of the short-term death of the patients is improved. A risk prediction model of short-term death of the patient suffering from the pyotoxic myocardial injury is constructed, so that a clinician can identify the patient suffering from the pyotoxic myocardial injury with high death risk in an early stage, a personalized treatment strategy can be formulated more accurately, the survival rate of the patient suffering from the pyotoxic myocardial injury is increased, and the method has a wide application prospect.

The invention of the gradient porous structured sacral prosthesis and the manufacturing process aims to create an alternative replacement for bone loss in patients who require bone replacement. The gradient porous structured sacral prosthesis consists of an artificial bone fragment, a metal rod, and a set of screws for fixing the fragments. The manufacturing process consists of seven steps: Identifying the position and boundaries of the bone, First-step topology optimization, Second-step topology optimization, Defining the structural pattern and unit cell size, Designing the artificial bone implant, Mechanical performance testing of the implant, and Fabrication of the sacral implant. The devices and processes according to the present invention are clearly sequenced and characterized. Modification or change in the manufacturing sequence or use may reduce the capabilities of the present invention or make it unusable for the purposes of the present invention.