76 results about "Therapy intervention" patented technology

The invention relates to the technical field of intelligent medical treatment, and discloses an AI-based severe patient sepsis early warning method and system. According to the method, a multi-organ interaction mechanism is deeply analyzed by dynamically constructing an organ-level causal network, and early-stage accurate early warning of sepsis is realized: high-frequency physiological waveforms, asynchronous laboratory indexes and treatment intervention data are fused, and the capture ability of microcirculation failure and autonomic nerve decline is improved; the early warning threshold value is dynamically adjusted based on the treatment coverage degree, and the delay and false alarm defects of a fixed threshold value mechanism are effectively overcome; a pathogen targeted therapy map and an organ function support scheme are automatically generated by a graded triggered clinical action chain, and the clinical decision response time is shortened; according to the method, the risk of missed diagnosis is reduced while the early warning sensitivity is improved, and an earlier and more reliable intervention window is provided for critical patients.

A medical monitoring system comprises a wearable garment incorporating multiple physiological sensors for real-time patient monitoring. The garment integrates an embedded processing unit that receives sensor data and transmits it wirelessly to a base station or remote server. A multi-modal physiological signal processing unit analyses the data to generate composite physiological indices, including metabolic rate, work of breathing, and fall risk assessments. The garment includes optional monitoring features such as transcutaneous carbon dioxide measurement, electrocardiography, pulse oximetry, blood pressure monitoring, and accelerometer - gyroscope-based motion tracking. The system provides early-warning alerts for clinical deterioration, enabling proactive therapeutic interventions. A wireless communication module ensures real-time data transmission, supporting remote monitoring and integration with hospital networks. The garment's modular design allows for non-invasive physiological assessment while maintaining patient mobility, making it suitable for critical care, ambulatory monitoring, and telemedicine applications.

A system and method for stimulating the activation of neural mirroring mechanisms through personalized avatars to enhance learning and skill development. The system creates hyper-realistic or stylized digital representations of users and animates these avatars to present educational content or demonstrate skills, stimulating mirror neuron activation when users observe themselves demonstrating mastery. Applications include academic learning, language acquisition, professional training, personal development, athletic performance enhancement, and therapeutic interventions including for Autism Spectrum Disorder.

The present invention provides a sensitive, accurate, bioactive skin barrier / wafer usable in ostomy systems and wound drainage collectors for identification of pathogens at critical thresholds of presence on peristomal skin at stoma sites and exuding wounds before clinical signs and symptoms of infection present. A method of fabricating a bioactive skin barrier / wafer intended for identification of pathogen presence in ostomy systems is provided, that delivers a rapid response observable alert. The present invention utilizes biomarkers to detect pathogens in real time, where biomarkers are characteristics objectively measured as indicators of health, disease, or a response to an exposure or intervention, including therapeutic interventions.

The invention discloses an AI-based atrial fibrillation patient health risk prediction method, and belongs to the technical field of medical information, and the method specifically comprises the steps: receiving a physiological parameter record and an intervention treatment record of an atrial fibrillation patient, carrying out the time sequence alignment operation, and forming structured patient data; extracting risk-related features from the structured patient data, wherein the risk-related features are divided into basic risk features and intervention response features; inputting the basic risk features into a basic risk prediction network, and outputting a basic risk score; inputting the intervention response characteristics and the basic risk score into an intervention effect separation network together to generate a post-intervention risk score; calculating a net effect value of treatment intervention according to the difference between the basic risk score and the post-intervention risk score; combining the basic risk score, the post-intervention risk score and the net effect value to generate a patient individualized long-term risk prediction trajectory; and accurate prediction of the long-term health risk of the atrial fibrillation patient is realized.

The disclosed method and system pertain to stratifying a patient population for precision medicine in Inflammatory Bowel Disease (IBD) treatment. The method involves accessing a multi-omic dataset comprising genomic, transcriptomic, and proteomic profiles of patient data. Machine learning algorithms are employed to analyze the dataset and identify biomarkers associated with a response to a drug for treating IBD. The patient population is stratified into phenotypic groups based on the identified biomarkers using unsupervised clustering. A patient population predicted to respond to the drug is defined based on the stratification and further analysis of patient metadata. The system includes a data storage unit and a processor configured to perform the method. The method and system can be used to optimize therapeutic interventions in IBD management.

A prediction system includes: a terminal; and a processor, communicatively coupled to the processor. The processor is configured to: acquire medical treatment information including images captured at at least one of before, during, immediately after, and after a predetermined period from treatment of a patient with a symptom of a vascular disease; classify a condition of the patient based on a classification image; learn the medical treatment information in association with the condition of the patient; and predict at least one of a treatment effect and a prognosis when treatment intervention is performed for the patient based on a learning result.

The invention provides application of dynamic cortex inhibition imbalance in clinical progress prediction of early Parkinson's disease. The key function of bilateral cortex inhibition balance in adjusting the motion compensation ability of the Parkinson's disease in the early stage is clarified. By analyzing the change of the two inhibition pathways, the change of delta SICI ' / LICI' is found to be a sensitive index capable of predicting the disease progress of the patient with the early Parkinson's disease. ROC results show that the delta SICI ' / LICI' has very high discrimination capability in the aspect of predicting disease progression, the area under curve (AUC) is 0.841, the sensitivity is 87.5%, the specificity is 72.73%, and the Eyden index is 0.602. The research of the invention makes deeper understanding of the pathophysiological mechanism of Parkinson's disease, and highlights the importance of cortex inhibition balance in disease evolution. These observations also support the development of more targeted therapeutic interventions to alleviate symptom progression.

Provided is a method of digital therapeutics for modulating one or more Parkinson's disease-related markers, symptoms, or disease progression in an individual, on a standalone basis or by combining them with medicinal agents, particularly dopaminergic agents. Also provided are corresponding systems for implementing, delivering, and adapting such therapeutic interventions.

An electronic system for multimodal diagnostic measurements and therapeutic interventions includes a plurality of element network layers vertically stacked one with another on a flexible substrate, each element network layer being bi-axially stretchable and comprising a plurality of elements configured in an addressable, interconnected array formed in a multilayered structure and operably performing a distinct function. The electronic system is a multimodal, multiplexed soft electronic system in a multilayered configuration that supports capabilities ranging from high-density spatiotemporal mapping of temperature, pressure and electrophysiological parameters, to options in programmable high-density actuation of thermal inputs and / or electrical stimulation, drug elution, radio frequency ablation, and / or irreversible electroporation ablation.

Some embodiments provide for a method for identifying an intervention for a subject in furtherance of preventing development of cardiovascular disease in the subject, the method comprising: obtaining cardiometabolic health data for the subject; determining, using at least some of the cardiometabolic health data, a first trained machine learning (ML) model and for each of multiple time intervals, one or more measures of risk that the subject develops cardiovascular disease to obtain multiple measures of risk; determining, using the multiple measures of risk that the subject develops cardiovascular disease and at least one second trained ML model, benefit of administering to the subject one or more therapeutic interventions designed to reduce risk of cardiovascular disease by targering one or more modifiable causes of the cardiovascular disease; and identifying, using the determined benefit of administering the therapeutic intervention(s), at least one therapeutic intervention to recommend being administered to the subject.

Certain disclosed embodiments relate to a physiological parameter monitoring system. The system may include a sensor and sensor electronics connected to the sensor. The system may also include a transmitter operably connected to the sensor electronics. The transmitter is positioned or configured to be positioned at a first location, at least a portion of which is adjacent and / or in contact with an external surface of the host's body during a sensor session, and is further configured to wirelessly transmit sensor information using intrabody communication. The system may also include a first display device including a display and a receiver. The receiver is positioned or configured to be positioned at a second location, at least a portion of which is adjacent and / or in contact with an external surface of the body during a sensor session, and is further configured to receive sensor information from the transmitter using intrabody communication.

A patient's health is modeled through multiple scenarios. A base model incorporates rules that govern a response by a human being to one or more diseases, as well as a relation between health metrics and the diseases. Health attributes of the patient are obtained. From the base model and the health attributes, a patient model is generated. The patient model is modeled under different parameters to generate health metrics. From an analysis of the parameters and the resulting health metrics, occurrence probabilities for each of the sets of parameters are determined. Risks are identified, which indicate a likelihood of the patient transitioning from the initial state to an adverse outcome such as a diseased state. A report provides a diagnosis of the patient and one or more remedies / interventions that are predicted, based on the plural sets of parameters and resulting health metrics, to avoid or prevent an adverse outcome.

Provided is a method of digital therapeutics for modulating one or more Parkinson's disease-related markers, symptoms, or disease progression in an individual, on a standalone basis or by combining them with medicinal agents, particularly dopaminergic agents. Also provided are corresponding systems for implementing, delivering, and adapting such therapeutic interventions.

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

The present invention provides a pneumoperitoneum maintenance device that facilitates the retention of air-filled material within a body cavity. [Solution] According to various embodiments, a probe can be inserted into a body cavity to perform a diagnostic intervention, a therapeutic intervention, or both. The probe can be inserted through a naturally occurring or artificial, intentional, or accidental body opening. The body opening can form a seal surrounding the probe, thus effectively holding the insufflation device within the body cavity and allowing the operator to perform the intervention. However, there may be leakage of the insufflated material. The insufflation holding device is configured to contact and form an effective seal adjacent to the body opening, providing a passage for introducing the probe into the body cavity, thus enabling a diagnostic or therapeutic intervention, or both.

Described herein are examples of systems and methods for determining the efficacy of a therapeutic intervention related to the treatment of diabetes. In an example, a continuous glucose monitor can be used to monitor the glucose levels of a subject. An insulin pump can administer insulin to the subject in response to the glucose levels obtained by the continuous glucose monitor. The efficacy of a treatment intervention can be determined by comparing an amount of insulin administered to the subject by the insulin pump over a timeframe associated with the treatment intervention to an amount of insulin administered to the subject by the insulin pump over a timeframe associated with a control or placebo period and / or a timeframe associated with a second treatment intervention.

There is provided herein a method of treatment comprising: (i) a first treatment cycle comprising administration of a therapeutically effective amount of a therapeutic agent, or a pharmaceutically acceptable salt thereof, to a subject in need thereof, wherein the therapeutic agent directly or indirectly induces muscle wasting; and (ii) a second treatment cycle following the discontinuation of the first treatment cycle, wherein the second treatment cycle comprises administration of a therapeutically effective amount of a β2-adrenergic receptor agonist, or a pharmaceutically acceptable salt thereof, to the subject, wherein the first and second treatment cycles are within the same therapeutic intervention.

The application relates to the technical field of medical devices and particularly discloses a pain dynamic evaluation and treatment linkage system based on three-dimensional somatosensory interaction, which comprises the following modules: a human body modeling module for constructing a three-dimensional human body dissection model; a somatosensory interaction module for receiving pain area marking instructions and pain intensity scores; an infrared sensing module for monitoring human body infrared thermal imaging data of a patient in real time; a physiological monitoring module for monitoring heart rate variability indexes and skin electric reaction indexes of the patient based on wearable devices; a region marking module for obtaining a calibrated pain area of the patient based on the pain area marking instructions and abnormal temperature zones in the human body infrared thermal imaging data; a pain prediction module for predicting a pain intensity prediction curve in a future period based on the pain intensity scores, the heart rate variability indexes, the skin electric reaction indexes and the calibrated pain area of the patient; and a treatment linkage module for generating treatment parameter control instructions based on the pain trend prediction curve and a multi-dimensional pain characteristic vector, so that precise and dynamic treatment intervention is realized.

The present invention executes a process based on cognitive behavior therapy for chronic diseases by means of a treatment assistance application installed on a patient terminal 1 for use by a patient. As a functional configuration for executing the process, a treatment assistance device comprises: a provocation content presentation unit 111 for presenting, to the patient and on the patient terminal 1, a content that provokes a symptom or a negative feeling; a reaction information acquisition unit 112 for acquiring information indicating a reaction from the patient during or after the presentation of the provocation content, through an input operation by the patient to the patient terminal 1 or a detection process by the treatment assistance application; and an intervention process determination unit 113 for determining, on the basis of the acquired reaction information, a treatment intervention process to be executed. As a result, the need for using a VR / AR projection device as a means for presenting the provocation content is eliminated, and the need for using an electroencephalograph or a specialized medial apparatus as a means for acquiring the reaction information from the patient with respect to the presentation of the provocation content is also eliminated.

A method for developing novel drug therapies utilizing properties of existing drug therapies, the method comprising the steps of: developing a novel therapeutic mathematical model of a target biological network and synthesizing a drug therapy based on the novel therapeutic mathematical model. The novel therapeutic mathematical model is capable of generating novel therapeutic time-course progressions, which include time-course progression features found in existing therapeutic time-course progressions of existing therapeutic mathematical models of the target biological network. The time-course progression features can be correlated with the outcomes of the target biological network. Each new therapeutic intervention constant can be used to synthesize a drug regimen, and these drug regimens collectively constitute the novel drug therapy.

A bioresorbable acoustic microrobot (BAMs) designed for precision medicine applications. Fabricated through two-photon polymerization, BAMs incorporate 7-diethylamino-3-thenolycoumarin, poly(ethylene glycol) diacrylate, pentaerythritol tetraacrylate, and Fe3O4 nanoparticles for magnetic steering, alongside encapsulated therapeutic agents. These microrobots feature an asymmetric dual-opening bubble-trapping cavity, enhancing acoustic propulsion and ultrasound imaging capabilities. The unique dual-surface layer chemistry ensures efficient operation in biological fluids, while hydrolysis-driven biodegradability minimizes residual harm. BAMs demonstrate sustained drug release, precise navigation, and effective tumor targeting, offering significant advancements over conventional microrobots in therapeutic interventions.

Electrophysiologic biomarkers for prognostication of neurological outcome are described herein. An inverse correlation was found between timing of a cortical spreading depolarization (SD) wave and neurological outcome as tested at 24 hours post-CPR. Additionally, a minor image of this SD was identified as a “repolarization (RP) wave.” Quantifying features of SD and RP during cardiac arrest and cardiopulmonary resuscitation (CPR) provide important metrics for diagnosis and prognosis of neurological injury from hypoxia-ischemia and can serve as an early prognostication tool for predicting outcome at subsequent days after successful CPR. This discovery may also allow for novel therapeutic interventions to improve neurological recovery after hypoxia-ischemia insults.

The present disclosure provides methods for determining a probability that after any of a number of therapeutic interventions, an initial state of a subject, such as somatic cell mutational status of a subject with cancer, will develop a subsequent state. Such probabilities can be used to inform a health care provider as to particular courses of treatment to maximize probability of a desired outcome for the subject.

Methods, systems, and compositions of matter for detection, analysis and treatment of biological, chemical and radiation exposure using artificial intelligence-based systems including fuzzy logical and / or machine learning. A system capable of compiling physical, biochemical, hematological, psychological and neural datapoints, analyzing said data points and creating actionable therapeutic interventions in a graded manner based on invasiveness and probability of success. Optimized biological intervention to chemical, radiation and biochemical threats using stem cells, T regulatory cells and induced pluripotent stem cells.

A system for assessing pressure injuries in a healthcare facility. The system creates patient metadata for a patient and associates the patient metadata with medical equipment including a patient support apparatus having a controller that performs pressure injury prevention functions and a surface positioned on a frame of the patient support apparatus. The system records usage data from the medical equipment via a network interface. The usage data including duration and frequency measurements of pressure injury prevention functions. The system receives sensor data from sensors positioned on the patient support apparatus. The sensor data includes weight distribution and patient movement measurements. The system pairs the usage data and the sensor data to the patient metadata to create survey data that correlates patient risk factors with therapeutic interventions performed by the medical equipment and stores the survey data in a database accessible for automated completion of a survey.

A self-contained extended reality (XR) device is disclosed for real-time detection and mitigation of substance use disorder symptoms. The headset includes integrated biometric sensors for capturing physiological signals such as pupil dilation, heart rate, and head movement. A locally stored machine-learned model analyzes these signals to classify cognitive or affective states indicative of withdrawal, craving, or relapse risk. Upon detecting a threshold state, the headset automatically renders an immersive therapeutic environment selected to mitigate the user's condition. Interventions may include spatialized audio, visual modulation, and avatar-guided interactions. The device further supports adaptive personalization, secure local data storage, and optional transmission of session summaries to authorized care providers. The system operates without external computing devices and is optimized for privacy-preserving, user-specific behavioral health support.

This information processing device comprises a model acquisition unit, a data of interest acquisition unit, and a determination execution unit. The model acquisition unit acquires a trained model in which medical record data before or during intervention of a predetermined treatment for patients with a specific disease is set as an explanatory variable and the necessity of palliative care for the patients is set as an objective variable. The data of interest acquisition unit acquires medical record data for a patient of interest. The determination execution unit: determines the necessity of palliative care for the patient of interest by inputting the medical record data for the patient of interest to the trained model; and causes an output device to output the result of the determination.