16 results about "Medical software" patented technology

The invention discloses a plateau newborn rare disease multi-mode combined screening system and a storage medium, and belongs to the technical field of medical software development. The plateau adaptability newborn rare disease multi-mode combined screening system is constructed, the plateau adaptability of the screening system is enhanced, the cost is remarkably reduced, and the screening system has a good application prospect.

The invention belongs to the technical field of medical software development, and particularly relates to a plateau newborn inherited metabolic disease screening system, a computer readable storage medium and application of the plateau newborn inherited metabolic disease screening system. According to the screening system, an altitude hierarchical multi-level reference value database based on a local healthy newborn queue is established, and the problem that the false positive rate of a plain area screening model in a plateau area is too high is solved by fitting an altitude metabolism marker reference median and a standard deviation curve. By designing a'biochemical primary screening-risk scoring-targeted sequencing automatic triggering 'three-level joint control data processing flow, targeted sequencing guided by a crowd specific pathogenic mutation library is started only when the biochemical risk is high, unnecessary whole genome sequencing is avoided, and the screening cost is remarkably reduced. The system can continuously iterate a reference curve and a risk threshold value according to definite diagnosis data, and closed-loop dynamic optimization from sample collection to report generation is achieved. The method has plateau adaptability, crowd specificity and cost controllability, and has a good clinical application prospect.

Apparatuses, systems, and techniques providing isolated execution of software-as-a-medical device (SaMD) applications on edge-AI platforms are provided. A criticality level of an application of a plurality of applications associated with a medical device is identified. Based on the criticality level, the application is determined to be executed in one of a plurality of environment. Each environment of the plurality of environments provides a corresponding level of isolation from other applications of the plurality of applications. One or more computing resources are assigned to the application, based at least on the criticality level or resource requirements of the application.

Medical software tools platforms utilize a surgical display to provide access to specific medical software tools, such as medically-oriented applications or widgets, that can assist surgeons or surgical team in performing various procedures. In particular, an endoscopic camera may register the momentary rise in the optical signature reflected from a tissue surface and in turn transmit it to a medical image processing system which can also receive patient heart rate data and display relevant anomalies. Changes in various spectral components and the speed at which they change in relation to a source of stimulus (heartbeat, breathing, light source modulation, etc.) may indicate the arrival of blood, contrast agents or oxygen absorption. Combinations of these may indicate various states of differing disease or margins of tumors, and so forth. Also, changes in temperatures, physical dimensions, pressures, photoacoustic pressures and the rate of change may indicate tissue anomalies in comparison to historic values.

The invention relates to the technical field of medical software, and discloses a myopia risk prediction method and system based on an eye biological parameter joint model, and the method comprises the steps: obtaining at least one time of eye biological parameter measurement data of a target individual, and the eye biological parameters comprise the eye axis length and corneal curvature data used for calculating the axis ratio; based on the eye biological parameter measurement data of the target individual, processing through a pre-trained myopia risk combined prediction model to obtain myopia occurrence risk information of the target individual in a future preset time period; and outputting myopia occurrence risk information of the target individual in the future preset time period. According to the method, the longitudinal sub-model and the survival sub-model share the random effect parameters, so that the calculation process of the myopia occurrence risk can reflect the individual difference information contained in the axis ratio change track of the target individual.

This invention relates to the field of medical software technology and discloses a method and system for predicting myopia risk based on a joint model of ocular bioparameters. The method includes: acquiring at least one measurement of ocular bioparameters of a target individual, wherein the ocular bioparameters include axial length and corneal curvature data used to calculate the axial ratio; processing the ocular bioparameter measurement data of the target individual using a pre-trained joint myopia risk prediction model to obtain myopia risk information for the target individual within a predetermined future time period; and outputting the myopia risk information for the target individual within the predetermined future time period. This invention shares random effects parameters between a longitudinal sub-model and a survival sub-model, enabling the calculation process of myopia risk to reflect the individual differences contained in the trajectory of axial ratio changes of the target individual.

The application discloses a highland newborn rare disease multi-mode combined screening system and a storage medium, and belongs to the technical field of medical software development. The application constructs a highland adaptive newborn rare disease multi-mode combined screening system. The screening system has highland adaptability, a significantly reduced cost, and a good application prospect.

The invention relates to the technical field of medical software, and discloses an intelligent follow-up visit robot system for a posthepatic transplantation transition period of children, which comprises a robot body, a communication module, and a parent terminal and a transplantation center follow-up visit system which are in communication connection with the robot body, a compliance prediction module; an ecological instantaneous evaluation module; and the ecological instantaneous intervention module is used for automatically triggering intervention measures of corresponding levels according to the follow-up state evaluation result and a preset grading intervention strategy. The ecological instantaneous evaluation module and the ecological instantaneous intervention module work cooperatively based on the same real-time data stream, so that the intervention content, the intervention opportunity and the intervention intensity can be adaptively adjusted along with the dynamic change of the medication compliance and the psychological behavior state of the child patient.

Disclosed are systems, methods, and articles for determining compatibility of a mobile application and operating system on a mobile device. In some aspects, a method includes receiving one or more data values from a mobile device having a mobile medical software application installed thereon, the data value(s) characterizing a version of the software application, a version of an operating system installed on the mobile device, and one or more attributes of the mobile device; determining whether the mobile medical software application is compatible with the operating system by at least comparing the received data value(s) to one or more test values in a configuration file; and sending a message to the mobile device based on the determining, the message causing the software application to operate in one or more of a normal mode, a safe mode, and a non-operational mode.

This invention relates to the field of medical software development technology and discloses a system and storage medium for differentiating benign and malignant pulmonary nodules based on cfDNA methylation-radiomics-clinical studies. The system includes a multimodal data acquisition module, a feature extraction and alignment module, a multimodal fusion diagnosis module, and an interpretable report generation module. After collecting clinical information, low-dose CT images, and peripheral blood cfDNA methylation sequencing data from the subjects, features are extracted from each modality and mapped to a unified semantic space through contrastive learning. A collaborative attention mechanism is then used to dynamically weight and fuse the aligned multimodal features. The fused features are input into a deep neural network classifier to output a nodule malignancy probability score, and finally, an interpretable diagnostic report with risk stratification is generated. This invention solves the problems of insufficient multimodal heterogeneous data fusion, poor model robustness, and weak interpretability, achieving accurate differentiation between benign and malignant pulmonary nodules, and demonstrating good clinical applicability and promotional value.

The present application belongs to the technical field of medical software development, and particularly relates to a highland newborn genetic metabolic disease screening system, a computer readable storage medium and an application thereof. The screening system establishes an altitude stratified multi-level reference value database based on a local healthy newborn cohort, solves the problem of high false positive rate of screening models in plain areas in highland areas by fitting altitude metabolic marker reference median and standard deviation curves. By designing a three-level control data processing flow of "biochemical primary screening-risk score-targeted sequencing automatic triggering", only when the biochemistry is high risk, the population-specific pathogenic mutation library guided targeted sequencing is started, unnecessary whole genome sequencing is avoided, and the screening cost is significantly reduced. The system can also continuously iterate the reference curve and risk threshold according to the confirmed data, realize the closed loop dynamic optimization from sample collection to report generation. The present application has highland adaptability, population specificity and controllable cost, and has good clinical application prospect.

Disclosed are systems, methods, and articles for determining compatibility of a mobile application and operating system on a mobile device. In some aspects, a method includes receiving one or more data values from a mobile device having a mobile medical software application installed thereon, the data value(s) characterizing a version of the software application, a version of an operating system installed on the mobile device, and one or more attributes of the mobile device; determining whether the mobile medical software application is compatible with the operating system by at least comparing the received data value(s) to one or more test values in a configuration file; and sending a message to the mobile device based on the determining, the message causing the software application to operate in one or more of a normal mode, a safe mode, and a non-operational mode.

Medical software tools platform utilizes a surgical display to provide access to specific medical software tools, such as medically-oriented applications or tools, that can assist those in the operating room, such as a surgeon or surgical team, with a surgery. In particular, an optical sensor located within an endoscopic camera may register subtle differences in color characteristics reflected from a tissue surface and in turn transmit the information to a medical image processing system. Moreover, the new tools are intended to help surgeons better determine the boundaries between healthy and diseased regions during surgical procedures. Various tools are intended to be used in procedures where indocyanine green (ICG) fluorescent dye is used. Intraoperative fluorescence imaging is commonly used during minimally invasive procedures to enable surgeons to visualize tissue perfusion and anatomical structures. The term perfusion refers to the passage of blood and tissue fluid through the capillary bed. Intraoperative fluorescence imaging can also be used to improve visualization of vessels and structures, which, in turn, may reduce the risk of complications during minimally invasive surgeries.

The invention relates to the technical field of intelligent terminal inquiry, in particular to intelligent terminal inquiry medical software and a method thereof.The intelligent terminal inquiry medical software comprises a symptom-physical sign collaborative sensing module, a symptom-physical sign collaborative sensing module and a symptom-physical sign collaborative sensing module, establishing a collaborative perception matrix of symptoms and signs; the sign-guided symptom deep mining module is used for automatically triggering a targeted symptom inquiry process according to the abnormal physiological sign data and guiding deep mining of symptom information through the sign data; and the dynamic credibility weighted diagnosis module is connected to the sign-guided symptom deep mining module, performs credibility weighting on the symptom information based on the sign data, and generates a final diagnosis result according to the weighted multi-modal evidence. According to the method, the stability and the interpretability of diagnostic reasoning can be still kept under the scene that part of information is lost or the uncertainty is relatively high, and the clinical decision support capability is improved.

A hardware-anchored deployment and safety system for continuous learning artificial intelligence at the local hospital edge. The system safely receives globally approved AI updates and isolates them within an ephemeral sandbox enclave. A hardware bifurcator splits live patient data, subjecting the incoming model to a silent, hardware-enforced shadow execution phase. A local divergence comparator tests the shadow model's performance and forwards metrics to an efficacy threshold gate. The efficacy threshold gate evaluates the metrics against a Predetermined Change Control Plan (PCCP) Manifest stored in a Localized PCCP Vault. If local efficacy is proven, an autonomous transition gate physically swaps the models without diagnostic downtime. A hardwired symbiotic rollback circuit constantly monitors the newly deployed model's live performance, capable of bypassing the local operating system to force a sub-millisecond reversion to a prior algorithmic state if clinical safety thresholds are breached, ensuring zero-risk localization of globally evolving medical software.