36 results about "Patient record" patented technology

Systems and methods for de-identifying patient data are disclosed herein. In some embodiments, a method for de-identifying patient data includes receiving a patient record including one or more identifiers. The method can include generating a first de-identified record from the patient record using a first de-identification process. The first de-identification process can be configured to produce a first re-identification risk score. The method can further include receiving a request from a data recipient to access the first de-identified record. The method can also include generating a second de-identified record from the first de-identified record by using a second de-identification process. The second de-identification process can be configured to produce a second re-identification risk score lower than the first re-identification risk score.

The invention discloses a multi-modal feature fusion prediction method and system for early screening of Alzheimer's disease, and belongs to the technical field of brain disease prediction. The method comprises the following steps: acquiring multi-dimensional data containing cognitive test scores, brain image scanning results and biomarker concentration levels from a patient record database, and performing standardization processing to obtain a multi-dimensional data set in a unified format; key feature vectors are extracted through a dimensionality reduction analysis method to capture the covariant relation between cognitive test scores and brain image changes; when the reduction range of the cognitive test score exceeds a preset threshold value and the brain image displays an atrophy sign, a classification model is constructed through an integrated learning method to preliminarily classify abnormal signals; and fusing the biomarker concentration level to obtain an abnormal signal vector. According to the method, the accuracy and efficiency of early screening of brain diseases such as Alzheimer's disease are remarkably improved through accurate evaluation of key parts of the human brain, such as hippocampus.

A system and method of property collection management and architecture that can organize patient data while maintaining context is presented. The present disclosure provides for a database system implementing a ‘Property Collection’ as a collection of ‘property name’ and ‘property value’ pairs, which are used to describe a ‘data entity.’ Further, the present disclosure can provide for historical access to data to track data changes. The present disclosure solves the technological problem of accessing data having differing data for the same person. The immutable electronic health record data storage system solves the aforementioned technological problem by providing a blockchain, transaction blockchain API, serialization module, and a deserialization module, among others that can format, process, and store data in a Global Patient Record (GPR).

To provide a photographing support device capable of efficiently collecting photographs of an affected part while suppressing a load on a doctor.SOLUTION: The medical image processing apparatus includes a registration unit that registers a disease name of an imaging target, an acquisition unit that acquires medical information of a patient recorded in an electronic medical record, a determination unit that determines whether the disease name of the patient acquired by the acquisition unit matches the disease name of the imaging target registered by the registration unit, and a notification unit that performs notification for prompting a user to image an affected part in a case where the determination unit determines that the disease name of the patient matches the disease name of the imaging target.SELECTED DRAWING: Figure 2

Systems and methods herein provide for access control to information in electronic patient records. One method includes receiving a request from an entity for access to one or more of a plurality of electronic patient records, the records having been machine learned to identify patient information in the electronic patient records including personally identifiable information and protected health information. The method also includes determining a level of access of the entity, retrieving, from a database, the one or more electronic patient records requested by the entity, applying a rule to the retrieved one or more electronic patient records based on the determined level of access of the entity to mask, encrypt, show, etc. one or more elements in the one or more electronic patient records. In response to applying the rule to the retrieved one or more electronic patient records, the electronic patient records are transferred to the entity.

A system for managing liver disease, the system comprising an electronic medical record system comprising a plurality of patient records. The system comprising a patient management platform configured to access the electronic medical record (EMR) system to retrieve medical records of one or more patients, analyze the medical records to selectively identify data related to a liver condition, interface with one or more data analysis platforms configured to receive and analyze the data related to a liver condition. Based on analysis by the patient management interface and / or the data analysis platforms, a display is generated comprising: specific liver-related patient attributes and conditions, and at least one of: a liver health prognosis or a recommended treatment for addressing the liver condition corresponding to the one or more patients. The liver condition can comprise one or more of: cancer, cirrhosis, liver failure, fatty liver disease, steatosis, ischemia, and / or hepatitis.

A method that includes receiving patient-generated event data over a network from a patient device associated with a patient having an active digital therapy prescription for treating an underlying disease or disorder. The patient-generated event data is encrypted by the patient device and includes at least one timestamped event related to the active digital therapy prescription. In response to receiving the patient-generated event data, the method includes decrypting, anonymizing, and storing the anonymized patient-generated event data on memory hardware. The method further includes receiving a patient record request over the network from a healthcare provider (HCP) system that requests the patient-generated event data and includes an authentication token. In response to receiving the patient record request, the method includes retrieving and encrypting the anonymized patient-generated event data from the memory hardware using the authentication token. The method also includes transmitting the encrypted patient-generated event data to the HCP system.

A system for predictive monitoring of patient deterioration by temporal modeling of electronic health records, the system comprising: a housing defining an enclosed volume; a plurality of input interface units arranged on the housing and configured to receive electronic health data including physiological signals, laboratory measurements, and clinical observations from external medical devices; an analog-to-digital converter unit electrically connected to the input interface units and configured to convert received signals into digital data streams; a signal conditioning unit operationally connected to the analog-to-digital converter unit and comprising filtering, normalization, and scaling circuits configured to standardize heterogeneous data into a uniform data representation;a temporal buffer unit consisting of a plurality of storage registers arranged in a sequential configuration, wherein the temporal buffer unit is configured to store time-indexed data samples over a predefined observation interval to generate a temporally ordered data structure; a synchronization unit configured to generate clock signals and align incoming data streams into synchronized timeframes before storage in the temporal buffer unit; a matrix transformation processor electrically coupled to the temporal buffer unit, wherein the matrix transformation processor comprises parallel arithmetic circuits, including multipliers, adders, and accumulators, arranged to perform weighted transformations on the temporally ordered data structure to generate temporal feature representations;a storage unit with non-volatile memory elements configured to store weighting parameters corresponding to the temporal characteristics of physiological data; a sequence evaluation unit operationally connected to the matrix transformation processor, comprising comparator circuits, gradient calculation circuits, and threshold evaluation registers configured to determine temporal deviations, rate-of-change characteristics, and cumulative variations indicative of a deterioration in the patient's condition; a decision output unit configured to generate a deterioration prediction signal based on the outputs of the sequence evaluation unit, the decision output unit further comprising a display unit, an audible alarm unit, and a communication unit for transmitting alarm signals;and an energy management unit configured to supply regulated electrical power to all units within the enclosure, wherein the system is configured to continuously process temporally ordered electronic health data to generate predictive indicators of deterioration in patient condition in real time.

A cloud-based, query management and education system enables provider organizations to query and educate clinicians on how to clarify clinical documentation, resulting in more accurate reimbursement, public reporting, research and policy decisions. Query authors create compliant queries from stored templates which may be supplemented by attaching and / or annotating selected documentation from the patient record. Clinician responses to such queries automatically generate addenda in the relevant patient record. All events around a query are tracked and reportable through a graphical performance scorecards and reporting dashboards.

This invention relates to the field of medical information and discloses a method for the digital archiving and management of historical radiology images. The method includes the following steps: acquiring and digitizing historical radiology film images and associated text information; generating enhanced digital archives with standardized metadata and establishing patient associations with existing image archiving and communication systems; adaptively generating spatially standardized mapping representations at different levels based on evaluation results; performing context-aware depth comparison and quantitative analysis of historical and current images during clinical retrieval; and generating structured reports based on the results of the depth comparison and quantitative analysis. By using intelligent graph matching and Bayesian inference with the deep semantic features of historical images and information from the existing system, high-precision and automated association between historical images and current patient records is achieved. Furthermore, by constructing hierarchical spatial mapping representations, the transformation of historical images from static archives into computable and quantifiable intelligent assets is realized.

Systems and methods for a virtual sonography team are described. An ultrasound system includes an ultrasound scanner that is configured to generate ultrasound data based on reflections of ultrasound signals transmitted by the ultrasound scanner and communicate the ultrasound data over a communication network to at least one display device and an archiver. An ultrasound machine is coupled to the ultrasound scanner and is configured to determine examination data for the ultrasound examination and communicate the examination data to the archiver over the communication network. The display device is configured to generate an ultrasound image based on the ultrasound data as part of an ultrasound examination and communicate the ultrasound image to the archiver for aggregation with the examination data into a patient record of the ultrasound examination.

In an illustrative embodiment, a system for providing automation and virtual assistance to medical claims processing includes a predictive analytics platform configured to receive patient information for a medical claim from a claims processing system, cross-reference the patient information with stored data to identify a patient record, apply the patient information to machine learning classifier(s) to estimate a likelihood of match between the patient information and the patient record, provide patient record information to the claims system, receive claims data from the claims system, access, from a data universe, requirements corresponding to a payer corresponding to the medical claim, the requirements having been generated through training machine learning classifier(s) with claims data corresponding to claims denied by the payer, verify the claims data in view of the requirements, and provide an indication of missing claims information and / or invalid claims information to the claims system.

The invention provides a personalized rehabilitation scheme intelligent generation method and system, and relates to the technical field of rehabilitation treatment, and the method comprises the steps: collecting multi-modal data of a patient, including skeleton joint point data, motion sequence data, physiological data and electronic medical record data, and carrying out the fusion to generate a structured file; calculating a first motion quality score based on the articulation point skeletal data; calculating a second exercise quality score based on the physiological data and the exercise sequence data; fusing the two types of scores through a modulation sorting average method to generate a comprehensive exercise evaluation report; then, in combination with patient archives and expert resources, a multi-objective optimization model with the maximum rehabilitation effect and the minimum resource cost as objectives is constructed, an optimization solver is used for solving, and a personalized rehabilitation scheme is generated; and finally, the personalized rehabilitation scheme is deployed to a remote rehabilitation platform, and closed-loop optimization control is realized by combining real-time data dynamic adjustment.

Embodiments can enable coordinated access to electronic medical records (EMRs) by mobile devices in communication with an EMR coordination server over a communications network, thereby integrating the EMR access into the physician's workflow. The EMR coordination server can receive a schedule request for a physician via the mobile device, and can identify appointments associated with the physician. Each appointment can be associated with a patient, an EMR server identified as having the patient's records, and a network location and EMR schema. The physician can select an appointment to access associated fields. The fields can be populated with fresh data from the identified EMR server, accessed by its network location, and mapped according to its EMR schema. Field data can be updated by physician dictation (or otherwise) and dictated audio can be automatically transcribed. Embodiments can operate even in context of multiple EMR servers having multiple EMR schemas and / or network locations.

A communication that is associated with a subject is accessed via an interface. One or more clinical concepts are determined based on the communication by using natural language processing and an ontological knowledge graph, where the ontological knowledge graph defines semantics, constraints, and relationships between a plurality of terms. An electronic health record is queried using the one or more clinical concepts. In response to the query, a set of records corresponding to the one or more clinical concepts from the electronic health record is received. An output is generated based on the set of records by using a generative artificial intelligence (GenAI) model, where the output comprises a summary of the set of records, a trend, or a categorization of information of the set of records. The interface is updated with the output.

Described is a system for receiving a disease specific treatment algorithm corresponding to a disease of a patient from a first Electronic Health Record (EHR) system, processing data corresponding to the disease specific treatment algorithm using a Large Language Model (LLM), receiving one or more CQL models from the LLM based on the processing of the data corresponding to the disease specific treatment algorithm, receiving an update to a patient record of the patient from the first EHR system, based on the update to the patient record and the one or more COL models, triggering a Clinical Decision Support (CDS) hook to generate an alert, and causing transmission of the alert for a medical practitioner associated with the first EHR system.

1. The name of the design product: electronic device's vasomotor symptom severity record graphical user interface. 2. The use of the design product: for an electronic device. 3. The design points of the design product: in the graphical user interface. 4. The picture or photo that best indicates the design points: design 1 interface change state diagram 2. 5. The usual design, omit other views of the electronic device. 6. Design 1 is designated as the basic design. 7. The use of the graphical user interface: for patients to record the severity of symptoms of vasomotor symptoms. 8. Other circumstances that need to be explained: the user clicks on any one of the buttons representing the degree of "mild", "moderate" and "severe" according to the degree of hot flashes in the main view of design 1, the interface jumps to design 1 interface change state diagram 1, clicks on the "confirm" button of the pop-up window in design 1 interface change state diagram 1, the interface jumps to design 1 interface change state diagram 2; the human-computer interaction mode of design 2 is the same as that of design 1.

Disclosed is a medical system that allows a healthcare professional to view medical records as they are associated with a patient avatar. The system may create a three- dimensional view of an avatar representing a patient and attach patient records to specific locations of the avatar as representative of the data within each record. A timeline of treatments may be accessible by selecting a particular position on the avatar corresponding to medical treatments.

An Integrated Virtual Patient Framework (IVPF) for providing decision support that evolves with increasing data collected on a given patient. Support decisions for patients with limited data is made using statistical prediction tools derived from historical trajectories of similar patients. As patient histories grow, decision support is provided by mathematical models that constrain the possible dynamics of the patient to more detailed predictive models. Weights for each model are assigned depending on uncertainties arising from data fitting and model properties. As new data are entered into a patient record, the models are recalibrated and the weights are adjusted, leading to updated decision support information. The framework also suggests the benefit of additional follow-up data collection events, optimizing the data collection as well as how the IVPF generates predictions. The framework also may present scenarios to patients in a way that informs them of treatment outcomes, given various strategies.

Abstract SYSTEM AND METHOD FOR PATHOLOGY SPECIMEN COLLECTION ADDRESSING NETWORK DISRUPTIONS AND DATA PRIVACY The present invention provides a system and method for pathology collection. A computer-implemented method for improved functioning of electronic pathology systems to overcome network disruptions is disclosed. This method encompasses receiving patient information and a list of requested medical tests, including the medical professional's identification, then determining suitable container types for the tests and generating a unique string encapsulating the test details, container indications, and patient information. The generated string comprising the decision tree indication and the scores assigned to each set of container indication. The generated string is further secured through encryption. Subsequently, a collector's device captures and processes this pattern, extracting and decrypting the necessary information using the corresponding public key. The container indications are presented to the collector, complete with images and quantities of required containers. A server and a computing device are also disclosed. Figure 1 Abstract SYSTEM AND METHOD FOR PATHOLOGY SPECIMEN COLLECTION ADDRESSING NETWORK DISRUPTIONS AND DATA PRIVACY The present invention provides a system and method for pathology collection. A computer-implemented method for improved functioning of electronic pathology systems to overcome network disruptions is disclosed. This method encompasses receiving patient information and a list of requested medical tests, including the medical professional's identification, then determining suitable container types for the tests and generating a unique string encapsulating the test details, container indications, and patient information. The generated string comprising the decision tree indication and the scores assigned to each set of container indication. The generated string is further secured through encryption. Subsequently, a collector's device captures and processes this pattern, extracting and decrypting the necessary information using the corresponding public key. The container indications are presented to the collector, complete with images and quantities of required containers. A server and a computing device are also disclosed. Figure 1 20 25 20 01 96 10 J an 2 02 5 A b s t r a c t S Y S T E M A N D M E T H O D F O R P A T H O L O G Y S P E C I M E N C O L L E C T I O N A D D R E S S I N G N E T W O R K D I S R U P T I O N S A N D D A T A P R I V A C Y 2 0 2 5 2 0 0 1 9 6 1 0 J a n 2 0 2 5 Fi gu re 1 C om pu tin g de vi ce R eg is te r f or a cc ou nt U pl oa d lis t o f o rd er ab le te st s St or ag e M ed ia Pa tie nt M ed ic al Pr of es si on al La bo ra to ry R ec ei ve te st li st R eg is te r f or ac co un t Se le ct a p at ie nt re co rd in C IS St ar t n ew pa th ol og y re qu es t R en de r in te rfa ce Q ue ry C IS fo r cu rre nt p at ie nt A Vi si t i n pe rs on o r vi rtu al ly B 10 2 10 0 10 4 20 0 20 2 20 4 20 6 30 0 30 2 30 4 40 0 Se rv er 10 1 / 9 20 25 20 01 96 1 0 Ja n 20 25 2025200196 10 Jan 2025 10 102 Computing Patient device 400 Visit in person or virtually 302 100 B Render interface A

The utility model relates to the technical field of grip balls, in particular to a visual counting grip ball. In order to solve the problems that although the exercise effect can be achieved, a patient cannot conveniently record standard exercise frequency, and irregular or nonstandard exercise is easily caused, the following technical scheme is provided: the training ball comprises a hollow ball body; the supporting mechanism is mounted in the ball body; the multiple sets of exercise assemblies are arranged on the supporting mechanism and used for providing elastic force for exercise; the multiple sets of pressing sensors are all installed in the supporting mechanism and correspond to the multiple sets of exercise assemblies respectively; and the adjusting mechanism is mounted in the supporting mechanism. Patients in all stages can exercise grip strength conveniently, standard exercise frequency is recorded accurately, rehabilitation exercise automation and standardization of the patients are improved, supervision blind areas of clinical medical workers are reduced, and the clinical medical workers can observe functional exercise of the patients conveniently and intervene in time to promote rehabilitation exercise of the patients.

A system and method for generating a 3D-printed medical appliance treatment plan and providing a set of 3D-printed medical appliances in accordance therewith, the method comprising: generating a dynamic 3D-printed medical appliance treatment plan generation model; obtaining a patient record; receiving 3D scanning data of the patient; generating a 3D-printed medical appliance treatment plan by applying the patient record and the 3D scanning data to the dynamic 3D-printed medical appliance treatment plan generation model; providing the 3D-printed medical appliance treatment plan to a medical practitioner; providing a manufacturing request to a manufacturer system for manufacturing a set of 3D-printed medical appliances; providing the set of 3D-printed medical appliances to the patient; receiving feedback from the medical practitioner regarding the 3D-printed medical appliance treatment plan; modifying the dynamic 3D-printed medical appliance treatment plan generation model based on the feedback.

Provided is a process including: obtaining, with one or more processors, a set of data comprising a plurality of patient records, selecting a subset of the plurality of parameters for inputs into a machine learning system, generating a classifier using the machine learning system based on the training data and the subset of the plurality of parameters for inputs; receiving, with one or more processors, patient record of a first user; performing an analysis, with one or more processors, to identify acoustic measures from a voice sample of the first user.

The embodiments disclose a system is disclosed for integrating regulated life sciences information into an electronic health record (EHR) workflow including one or more processors, non-transitory memory storing executable instructions, and an interface configured to communicate with at least one EHR system, during an active clinical workflow, the system authenticates a healthcare provider accessing a patient record and extracts one or more clinical triggers from the record, based on the extracted clinical triggers, the system selects at least one information object from a plurality of regulated life sciences information objects stored in a database, the selected information object is presented within a predefined region of an EHR workflow interface in a manner that does not interrupt the clinical workflow.

The invention discloses a self-management digital platform for orthopedic pain patients, which comprises a platform rear end, a doctor end and a patient end, and is characterized in that the patient end comprises an initial information recording module, a rehabilitation plan module, a medication reminding module, a knowledge base module, a doctor-patient communication module and a social module; the information recording module is used for recording the pain condition of the patient and forming a treatment file in combination with the contents of the rehabilitation plan module and the medication reminding module; the rehabilitation planning module is used for providing rehabilitation action guidance according to the pain condition of the patient; the medicine taking reminding module is used for reminding the patient to take medicine; the knowledge base module is used for providing popular science knowledge; and the doctor-patient communication module is used for remote interaction between the patient and the doctor. The platform helps the patient to autonomously manage pain, rehabilitation training and daily health behaviors, the patient can scientifically perform pain management through recording, planning and reminding, and the pain rehabilitation data of the patient can be provided to the rear end of the platform as big data for research to provide reference for other patients.

A portable home healthcare workstation defines a wheeled enclosure and telescoping, angled worksurface transportable to a patient home or domicile bedside. A telescoping handle extends for supporting the worksurface at a suitable height, and an angular pivot allows the worksurface to be oriented for ease of access to patient records or temporary storage of medical supplies. An accessory container attaches to the telescoped uprights and provides containment of equipment and supplies, and detaches for storage in the enclosure. A stabilizer extends horizontally from the uprights, and together with the attached enclosure and base provide support on opposed sides of the uprights for maintaining a substantially vertical orientation to support the worksurface. Retraction of the stabilizer allows the worksurface to be received in the enclosure for wheeled portability, and collapsing of the telescoped uprights allows for handcarry capability.

The present invention provides a doctor-seeing time prediction system for predicting a doctor-seeing call time of a subject patient, comprising: a storage device for storing and storing progress of a plurality of steps from reception of a call and actual performance data relating to a sample for each doctor-seeing; a processing device that, on the basis of the actual performance data, calculates an implementation prediction time for each process in which the subject patient sees a doctor, and predicts a doctor-seeing call time; and a database that records the predicted treatment call timing calculated by the processing device and that can be accessed from a terminal carried by the subject patient, the processing device being configured to process the treatment call of the subject patient after a portion of the process relating to the treatment of the subject patient has been completed, and the database being configured to store the predicted treatment call timing calculated by the processing device. On the basis of the actual performance data, an implementation prediction time is recalculated for an uncompleted process, and a doctor-seeing call prediction time of the subject patient recorded in the database is updated.

Method for acquiring magnetic resonance data of a target area of ​​a patient moving during respiration using a magnetic resonance device (1), wherein an optical camera (5) arranged in a patient recording of the magnetic resonance device (1) and directed towards the patient is used, wherein image data of the patient acquired by the camera (5) before and / or during the acquisition of the magnetic resonance data are evaluated to obtain respiratory information describing the respiratory state, characterized in that the respiratory information is used to trigger and / or correct movement and / or assess a breath-holding process of a patient, wherein a message is issued to an operator when an interrupted breath-holding process is detected during the acquisition of magnetic resonance data.

A facility for providing access to an electronic medical record instance receives a login attempt from a client device that provides login credentials. The facility uses these login credentials to access an account key associated with the login credentials, and retrieves from a patient link database a mapping from the accessed account key to a mapped-to record identifier and a mapped-to instance identifier. The mapped-to record identifier identifies a patient record maintained on an electronic medical record instance identified by the mapped-to instance identifier. The facility uses the mapped-to record identifier and mapped-to instance identifier to provide the client device access to the patient record having the mapped-to record identifier on the instance identified by the mapped-to instance identifier.

The application discloses a lossless medical image authentication method based on histogram stretching, utilizes an adaptive adjacent pixel interpolation expansion (AIA) technology to obtain seed pixels and non-seed pixels, regards pixel points of an input image A as seed pixel points, regards pixel points obtained through expansion as non-seed pixel points, the seed pixels remain unchanged during embedding, ensures reversibility of the scheme, balances embedding capacity and camouflage image quality at the same time, then carries out segmentation on the image to obtain a region of interest (ROI) and a non-region of interest (RONI), and finally embeds sensitive information such as electronic patient records (EPR) and electronic signatures of medical images as secret information, and adopts a corresponding bit histogram shift and repeat embedding method (CBHSR) in the region of interest. The application effectively avoids image distortion problems introduced by histogram stretching.