7874 results about "Internal medicine" patented technology

A noninvasive blood pressure monitor. The noninvasive blood pressure monitor may include an inflatable cuff, a pressure transducer, one or more air pumps, and a processor. The processor may control the air pump(s) so as to initiate inflation of the cuff. The processor may also identify an oscillometric signal in an output of the pressure transducer, and may determine an envelope of the oscillometric signal. The processor may also determine one or more characteristics of the envelope of the oscillometric signal, and may control the air pump(s) so as to stop inflation of the cuff based on the one or more characteristics of the envelope of the oscillometric signal.

Provided herein are epinephrine spray formulations. Also provided herein are methods of treating anaphylaxis by administering epinephrine spray formulations to subjects in need of such treatment.

The invention relates to a method for operating an implanted, ventricular assist system (2), comprising the following steps: a) determine a first impedance parameter at a first point in time by means of the assist system (2), b) determine a second impedance parameter at a second point in time by means of the assist system (2), c) at least determine a change of the impedance parameter using the first impedance parameter and the second impedance parameter, or compare at least the first or second impedance parameter to a threshold value.

Systems and methods for monitoring glucose levels of a user are described. Data indicative of glucose levels of the subject is received. A count is assigned for each glucose episode based at least on an area under the curve of the each glucose episode in a dataset of time-correlated glucose data. A running sum of counts for each glucose episode in a time period is calculated. The running sum of the counts may be displayed in a numerator of a fraction and a target count goal in a denominator of the fraction. A progress indicator representative of the running sum of the counts relative to a target count goal for the time period may also be displayed. A length of a variable portion may be proportional to the running sum of the counts, and a total length of the progress indicator may be proportional to the target count goal.

Systems and methods for monitoring glucose variability in a subject are described. Data indicative of glucose levels of the subject is received from a sensor control device. A first glucose variability metric of the subject in a first time period is determined. The first glucose variability metric may be compared to a threshold. A first indicator is displayed if the first glucose variability metric does not exceed the threshold and a second indicator is displayed if the first glucose variability metric exceeds the threshold. Additional glucose variability metrics may be determined for subsequent time periods according to a rolling window, and the indicators may be displayed real time or in a report. The glucose variability metric may be a measure of variability compared to a baseline, a difference between a maximum and minimum glucose level, or time in or out of a target range.

The invention relates to the field of disease prediction, in particular to an epilepsy prediction system based on synchronously acquired electroencephalogram-gastric electrical signals, comprising: a data acquisition module for acquiring data including electroencephalogram data and gastrointestinal electrical data; the first analysis module is used for obtaining an average electrode inconsistency index of the first channel and the second channel based on a first model according to the time sequence data; and the prediction module is used for comparing the average electrode inconsistency index of the subject with a preset evaluation threshold value so as to predict an epileptic. The system provided by the invention can more accurately and efficiently distinguish epilepsy patients from healthy people, and can be used as an auxiliary diagnosis tool to be applied to primary screening of epilepsy of relatively large people (such as communities and physical examination centers).

The invention belongs to the technical field of medical signal processing, and particularly relates to a heart sound and electrocardio combined coronary heart disease detection method based on time-frequency fusion, which comprises the following steps: S1, performing data preprocessing on PCG and ECG original signals, including noise reduction, baseline drift elimination, power line interference elimination and the like, and performing normalization processing on the PCG and ECG signals to obtain a normalized PCG and ECG signal; a Welch method is adopted to generate power spectrum signals of heart sound and electrocardio, and time domain signals and power spectrum signals of PCG and ECG are segmented into equal-length fragments. In order to effectively solve the problem of inaccurate diagnosis caused by poor single-modal data quality, a heart sound and electrocardio dynamic fusion module is constructed based on a time-frequency fusion result of two signals, dynamic weight distribution is carried out, a proper classifier is selected for classification, and the diagnosis accuracy is improved by supplementing frequency domain information. And the weight is distributed according to the contribution of the heart sound and the electrocardiosignal, so that the detection and classification result of the coronary heart disease is more accurate.

The invention relates to the technical field of biomedical signal processing and intelligent health monitoring, and particularly discloses an intelligent heart rate monitoring method and system based on heart sound and electrocardiosignals, heart sound signals and electrocardiosignals of a user are collected in real time, quality evaluation is conducted on the collected signals through signal quality indexes, and accurate signals are extracted; extracting time domain and frequency domain features of the first heart sound and the second heart sound of the heart sound signal, fusing multiple features by adopting wavelet transform and a main frequency analysis algorithm, and calculating a heart sound abnormal coefficient to evaluate the abnormal degree of the heart sound signal; the vibration amplitude and frequency characteristics of P waves in the electrocardiosignals are extracted, and an electrocardiograph abnormal coefficient is calculated through a vibration amplitude abnormal coefficient and a vibration frequency fluctuation coefficient and used for evaluating the stability of the electrocardiosignals; based on the heart sound abnormal coefficient and the electrocardiogram abnormal coefficient, a decision tree model is constructed, a heart rate abnormal index is dynamically calculated, dynamic monitoring of the heart rate is achieved, a dynamic early warning mechanism is conducted, and heart rate abnormal information is output.

The invention belongs to the technical field of diving state monitoring, and relates to a diver state monitoring method based on biofeedback, and the method comprises the steps: aligning a sign signal with environment data through a timestamp, extracting motion features through acceleration data, constructing a motion noise model, and removing signal artifacts in real time; in the aspect of EEG signal purification, a db4 wavelet basis is adopted for carrying out wavelet packet decomposition, water pressure related frequency band characteristics are extracted, low-frequency drift is removed, meanwhile, heart rate signals are analyzed through nonlinear dynamics, a Lyapunov index is extracted to evaluate HRV changes, breathing and EEG # imgabs0 # wave coupling are analyzed through wavelet transformation, and the risk evaluation precision is further enhanced; in the aspect of environment compensation, through compensation of a depth and SpO2 relational expression and water temperature on respiratory frequency, in combination with SLTM network extraction time sequence features and a deep causal convolutional layer, risk trend prediction is performed, a diver risk level and a prediction curve are output in real time, a comprehensive risk index is finally calculated, the health state and potential risk of the diver are comprehensively evaluated, and safety is improved.

The invention discloses a chronic disease intervention safety detection system and method based on large model multi-agent cooperation, and relates to the technical field of natural language processing and multi-agent cooperation in the medical health field. A standardized interface and an adaptive cleaning algorithm are adopted to realize data desensitization, missing value filling and format unification, and a dynamically updated patient health portrait is constructed; complex tasks are decomposed based on a chain reasoning technology, special tools such as a drug interaction detection tool and a nutrition gap calculation engine are developed, and a clinical knowledge base is integrated for parallel analysis; suggestion conflicts are eliminated through a multi-agent debate mechanism, the priority is calculated in combination with a weight rule, manual auditing is triggered to process low-confidence disputes, and finally a structured health report containing medication adjustment, diet optimization and behavior intervention is generated. The limitation of a traditional method in data integration, cross-domain reasoning and conflict resolution is solved.

The invention relates to the technical field of medical information analysis, in particular to a breast cancer disease science popularization method and system based on a multi-modal knowledge graph. The method comprises the following steps: acquiring and processing breast cancer image samples and text data; breast cancer specific features are extracted from the breast cancer image sample; in a knowledge graph, creating corresponding nodes for the breast cancer specific characteristics, and establishing a mapping relation with medical diagnosis information to form multi-modal unified representation; associating medical text entities in the text data with breast cancer specific feature nodes to form a multi-modal knowledge graph; and obtaining to-be-diagnosed information input by a user, retrieving the associated nodes related to the to-be-diagnosed information from the multi-modal knowledge graph, and outputting popular science content. According to the application, individuation, authority and interactivity of breast cancer science popularization can be realized, and high-quality science popularization service is provided for patients and the public.

The invention discloses a millimeter wave radar vital sign detection method based on an HHO-CEEMDAM algorithm, and the method comprises the steps: building a millimeter wave radar experiment system, and collecting an intermediate frequency signal of a human body echo; performing data reading and recombination, extracting phase features, and enhancing a target signal through non-coherent accumulation to determine the distance between the chest of the human body and the radar; recovering the phase of the vital sign signal from the incoherent accumulation FFT result by using the linear characteristic of arc tangent demodulation, and performing phase unwrapping and phase difference to obtain optimized phase information; setting a CEEMDAN parameter initialization range and designing a fitness function; a CEEMDAN parameter is optimized by using an HHO algorithm; performing CEEMDAN decomposition by using the optimized parameters, and screening breathing and heartbeat IMF components; and according to the IMF component, obtaining estimated values of the respiratory rate and the heart rate. The method improves the estimation precision of the respiratory rate and the heart rate of the millimeter wave radar in fatigue driving detection.

Provided herein are variant α4β7 integrin antibodies and methods of use.

The invention belongs to the field of food, and particularly relates to a nutritional composition containing probiotics and breast milk oligosaccharide for improving anxiety or depression and application of the nutritional composition. The invention provides application of a nutritional composition in preparation of food beneficial to improving constipation and anxiety state and / or depression state caused by constipation. Wherein the nutritional composition comprises the following components (i) and (ii): (i) a bifidobacterium probiotic, and (ii) a sialylated breast milk oligosaccharide; the bifidobacterium probiotics at least comprise animal bifidobacterium subsp. Lactis, the sialylated breast milk oligosaccharide at least comprises 6 '-sialylated lactose, and the animal bifidobacterium subsp. Lactis comprises a Bb-12 strain. The substance combination of the bifidobacterium probiotics and the sialylated breast milk oligosaccharide can synergistically improve abnormal brain-intestine interaction, and improve constipation and anxiety and / or depression state caused by constipation.

Systems and techniques to protect against abuses in the transfer and maintenance of tokens within NFT platforms are illustrated. One embodiment includes a method to facilitate filtration in blockchains. The method recovers, from a list of prospective entries to be appended to a primary blockchain, a reference to a blockchain entry. The method obtains a certainty level associated with the blockchain entry. The method assesses a classification of the blockchain entry based on the associated certainty level. The method determines whether to record the blockchain entry on the primary blockchain based on the classification.

The dynamic continuous blood glucose monitor comprises a needle assisting device assembly, the needle assisting device assembly comprises a main shell, a push rod base and a push rod, the push rod base and the push rod are movably arranged in the main shell, and an emission spring is arranged between the push rod base and the push rod; the needle assembly comprises a needle clamp and a needle seat which are fixedly assembled, and a needle withdrawing spring is arranged between the needle clamp and the push rod; and the bottom cover is detachably assembled on the main shell. The dynamic continuous blood glucose monitor has the advantages of being simple and reasonable in structural design and easy and convenient to operate, and during use, feeding and withdrawing of the auxiliary needle and smooth implantation of the sensor probe into the human body can be automatically completed only by pressing the main shell; the detachable bottom cover structural design avoids potential safety hazards caused by exposure of structures such as a CGM sensor and an auxiliary needle, and after the device is used once, when the device needs to be used again, a new CGM module is loaded below the main shell again, meanwhile, structures such as the push rod, the push rod seat and the needle clamp are reset, and the bottom cover is screwed back, so that the device is convenient to use. Therefore, the dynamic continuous blood glucose monitor can be reused, and waste is avoided.

The invention discloses a breast cancer prognosis real-time evaluation system and method fusing a multi-modal image and a co-disease network, and relates to the technical field of breast cancer prognosis evaluation. According to the system, a comprehensive feature matrix fusing images, genes and clinical features is constructed by acquiring a mammary gland medical image, extracting focus features and combining gene expression information of a focus area and co-disease data of a patient, feature weighting is carried out based on an attention mechanism, and finally a prognosis risk score is output by utilizing a multi-layer perceptron model. And risk grading and intervention suggestion generation are realized. According to the system, a co-disease network and a gene interaction network are introduced for modeling, relevance expression among multi-source information is enhanced, and pathological features and systematic health status of patients can be reflected comprehensively. The intelligent level of prognosis evaluation can be improved, and good clinical popularization value is achieved.

Provided is a method for treating and / or preventing of cancer using Compound A or a pharmaceutically acceptable salt thereof.

A medical apparatus for a patient comprises an external system and an implantable system. The external system is configured to transmit one or more transmission signals, each transmission signal comprising at least power or data. The implantable system is configured to receive the one or more transmission signals from the external system, and to deliver stimulation energy to the patient. Methods of delivering stimulation energy are also provided.

In a device and a method for obtaining a heart rate, the device for obtaining a heart rate may include: a processor; and a memory device, and obtain a first band image and a second band image in different bands, measure a first remote heart rate signal and a second remote heart rate signal for the first band image and the second band image, respectively, compute a first quality score and a second quality score for the first band image and the second band image, respectively, select a first effective heart rate section based on the first remote heart rate signal and the first quality score, select a second effective heart rate section based on the second remote heart rate signal and the second quality score, and determine a complementary heart rate based on the first effective heart rate section and the second effective heart rate section.

The invention discloses a colorectal cancer focus segmentation method based on improved TransUNet. The method comprises the following steps: collecting related pathological image data of a colorectal cancer patient; enhancing and expanding the data set by adopting a data enhancement technology, and adjusting and processing the image data; the method comprises the following steps: constructing a model, integrating a PEMA module at multiple positions of the model, introducing an EUCB up-sampling module into a decoder part, replacing standard convolution of the decoder part with lightweight dynamic convolution, and using a composite loss function MediBoundFusion Loss; the preprocessed training data set is input into the improved TransUNet network model to be trained; and the colorectal cancer focus is segmented by adopting the improved TransUNet network model after training is completed. The key problems that focus features are fuzzy, boundaries are difficult to define, forms are irregular, and effective features are difficult to extract due to low contrast of early cancerous tissues can be solved.

The embodiment of the invention provides an exercise heart rate detection method. The exercise heart rate detection method comprises the steps that an initial PPG signal and an initial ACC signal are obtained; filtering processing is carried out; calculating a resultant acceleration average value and an energy concentration degree; determining whether it is in a motion state; if not, determining heart rate information based on the time domain information; if so, judging whether a same-frequency condition exists or not; if yes, spectrum subtraction processing is carried out; and determining heart rate information in the PPG spectrum after spectrum subtraction processing and the PPG spectrum without spectrum subtraction processing based on a frequency tracking algorithm. According to the scheme, the motion state is judged more comprehensively and accurately, the heart rate information is determined based on the time domain information when the user is not in the motion state, the calculation amount is small, and the heart rate result can be obtained quickly. When the user is in the motion state, the same frequency condition between the ACC frequency spectrum and the heart rate at the previous moment is firstly judged, targeted spectrum subtraction processing is conducted on the PPG frequency spectrum, then the heart rate information is determined through a frequency tracking algorithm, motion artifact interference can be effectively eliminated, and the heart rate during motion can be accurately obtained.

The present disclosure relates to detecting one or more types of gynecological cancer in a biological sample from a subject. In particular, the present disclosure provides compositions and methods for detecting the presence or absence of one or more types of gynecological cancer (e.g., cervical cancer, ovarian cancer, endometrial cancer) in a biological sample of a subject suffering from or suspected of suffering from gynecological cancer.

The invention relates to an application of metformin in preparation of skin anti-photoaging drugs or medical instruments. Through verification, the metformin has the effects of promoting the formation of autophagosome, recovering the patency of autophagy flow and remodeling an autophagy-ECM metabolism regulation network. After the composition is applied to the skin (such as a corium layer), the effect of resisting skin photoaging is achieved by adjusting an AMPK signal channel. The metformin is used as an active ingredient to prepare a medicine or a medical instrument, and is beneficial to clinically anti-photoaging application of the skin.

The invention discloses a method and system for evaluating infusion operation of intern medical staff, and belongs to the field of infusion, and the method comprises the steps that the operation of the intern medical staff is collected in multiple modes, and the multiple modes comprise a visual mode, a touch mode and a physiological signal mode; inputting the collected operation of the intern medical staff into the multi-modal infusion evaluation model, performing feature extraction by the multi-modal infusion evaluation model in a modal manner, and performing cross-modal attention fusion on feature vectors of different modals; and finally, comparing the calculated total feature tensor Hfusion with a standard total feature tensor Hfusion ', and outputting a final score of the practice medical personnel according to a preset scoring standard. According to the scheme, multi-dimensional data such as visual, tactile and physiological signals are synchronously collected through a multi-modal fusion method, operation details are comprehensively covered, comprehensive evaluation is carried out, and evaluation objectivity is improved.

The invention discloses a tumor irreversible electroporation ablation simulation prediction system, which comprises the following modules: a simulation model geometric structure establishment module, which is used for determining related parameters of a tumor irreversible electroporation ablation operation and a catheter electrode structure, and establishing a geometric structure of a simulation model; the geometric model and numerical model setting module is used for setting a geometric model and a numerical model; respectively constructing a two-electrode plate type three-dimensional finite element multi-physical field simulation model and a three-electrode plate type three-dimensional finite element multi-physical field simulation model for irreversible electroporation ablation of tumors; the data set establishment module is used for respectively performing simulation calculation on the two numerical models constructed by the geometric model and the numerical model setting module; the model training module is used for training the respective data sets of the two numerical models obtained by the data set establishing module by using a random forest regression algorithm; and the simulation prediction module is used for predicting the tumor ablation condition and the damage condition of surrounding normal tissues. The system provided by the invention can accurately predict the tumor ablation condition and the damage condition of surrounding normal tissues.

A dietary supplement composition is formulated in a therapeutic amount to maintain and promote urinary and prostate function in a human. The composition includes a shelf stable, supercritical CO2 fluid extracted, enhanced lipidosterolic extract of Serenoa repens (LSESr). The enhanced LSESr has a ratio of free fatty acids to total fatty acids that is greater than about 83.0% and an enrichment of lauric, myristic, oleic and linoleic acids as free fatty acids to total free fatty acids that is about 81.0% or greater.

The invention discloses a method for evaluating postprandial blood glucose response of a human body based on continuous blood glucose data and application. The method comprises the following steps: acquiring a continuous blood glucose detection value and meal starting time; matching a first blood glucose recording point after eating according to the dining time, intercepting blood glucose data of 2 hours after meal, and preprocessing the data; constructing four postprandial blood glucose response modes by applying the continuous blood glucose data of FPCA and based on a characteristic function of which the interpretation degree ranks top two obtained by the FPCA; through comparison of postprandial blood glucose response mean value curves of the four blood glucose response modes, the four response modes can evaluate postprandial blood glucose by integrating the blood glucose concentration range and whether the fasting homeostasis can be rapidly recovered or not.

Aspects of the disclosure provides composition and methods for treating a subject having a blood loss condition, the method comprising administering to the subject a hemojuvelin (HIV) antagonist (e.g., anti-HJV antibody).

The invention discloses a lung squamous cell carcinoma survival prediction method and system based on SHAP interpretability, and relates to the technical field of medical data analysis. Comprising the following steps: constructing a dynamically updated physiological feature information table based on a lung squamous cell carcinoma clinical data set of a target under multiple time nodes; and associating different survival analysis models with the physiological feature information table to predict the survival probability of the lung squamous cell carcinoma in the target body, the marginal contribution of each input feature to the output of each model is obtained by using the SHAP interpretation algorithm, and the feature uniqueness score is transparently displayed in the fusion process, so that the survival probability of the lung squamous cell carcinoma in the target body can be predicted in the actual use process. The method can visually understand how each feature affects the final prediction, and achieves automatic arbitration or manual recheck through providing a model to explain conflict measurement, invalid variable elimination and pseudo high risk verification and weighted scoring, thereby guaranteeing the reasonability and safety of prediction and intervention suggestions, reducing the decision risk, and enhancing the clinical trust.