49 results about "Patient classification" patented technology

This disclosure provides an efficient, hands-free system and method for capturing and recording patient data in critical care environments. The systems and methods described herein enables clinicians to record and transcribe patient information onto a disposable medical record tag (akin to a military ID tags), which accompanies the patient throughout initial stabilization and presentation to a treatment center. A Pre-Hospital Treatment & Triage (PHT) guidance system, visible in the HMD, can guide caregivers and / or first responders through treating the patient and documenting a patient's medical condition and treatment status, and triaging patients to the appropriate level of care. The head-mounted display can wirelessly transfer the patient's treatment data to a lightweight disposable data tag, referred to as an electronic TCCC (E-TC3) that is affixed to the patient. The data tag digitally stores a patient's health status, and displays a specific color based on a patient's degree of injury.

A computer-implemented method for profiling medical claims to assist health care managers in determining the cost-efficiency and service quality of health care providers. The method allows an objective means for measuring and quantifying health care services. An episode treatment group (ETG) is a patient classification unit, which defines groups that are clinically homogenous (similar cause of illness and treatment) and statistically stable. The ETG grouper methodology uses service or segment-level claim data as input data and assigns each service to the appropriate episode. The program identifies concurrent and recurrent episodes, flags records, creates new groupings, shifts groupings for changed conditions, selects the most recent claims, resets windows, makes a determination if the provider is an independent lab and continues to collect information until an absence of treatment is detected.

A computer-implemented method for profiling medical claims to assist health care managers in determining the cost-efficiency and service quality of health care providers. The method allows an objective means for measuring and quantifying health care services. An episode treatment group (ETG) is a patient classification unit, which defines groups that are clinically homogenous (similar cause of illness and treatment) and statistically stable. The ETG grouper methodology uses service or segment-level claim data as input data and assigns each service to the appropriate episode. The program identifies concurrent and recurrent episodes, flags records, creates new groupings, shifts groupings for changed conditions, selects the most recent claims, resets windows, makes a determination if the provider is an independent lab and continues to collect information until an absence of treatment is detected.

A system and method for identifying and treating a disease in a patient collects one or more data streams from sensors configured to detect biological signals generated within a patient's tissue over time. Patient data elements including one or more of demographic, clinical, laboratory, pathology, chemical, image, historical, genetic, and activity data for the patient is collected and processed with the data streams to generate a personalized digital phenotype (PDP). The PDP is compared to a digital taxonomy comprising prior data to classify the patient into one or more quantitative disease classifications to guide personalized intervention for treating the patient.

The invention relates to a gene network analysis-based disease subtype prediction system. The system is divided into the following three modules: a data acquisition and preprocessing module; a patientclassification and disease subtype prediction module; and a result display module; the patient classification and disease subtype prediction module includes a gene network gene node vectorization sub-module, a disease patient vectorization sub-module, and a disease subtype prediction sub-module.

Disclosed are methods for classifying a patient with cancer as a candidate for therapy with a Bcl-2 family inhibitor comprising determining the level of at least one biomarker in a sample and comparing the biomarker level to a threshold level. Also described are methods for identifying classes of patients having a refractory cancer for second-line therapy comprising a Bcl-2 family inhibitor, where the method comprises determining the level of at least one biomarker in a sample and comparing the biomarker level to a threshold level.

A system and method for identifying and treating a disease in a patient collects one or more data streams from sensors configured to detect biological signals generated within a patient's tissue over time. Patient data elements including one or more of demographic, clinical, laboratory, pathology, chemical, image, historical, genetic, and activity data for the patient is collected and processed with the data streams to generate a personalized digital phenotype (PDP). The PDP is compared to a digital taxonomy comprising prior data to classify the patient into one or more quantitative disease classifications to guide personalized intervention for treating the patient.

A method, system and device for detecting an ocular dysfunction with optic neuropathy, such as the glaucoma group of diseases. More particularly, one eye is exposed to a series of flashes, and the resulting pupillary reflexes of both eyes are measured. The pupillary reflexes can then be evaluated to determine if the ocular dysfunction is present. A device that includes at least one light source can be incorporated into a system for recording and evaluating the pupillary reflexes.

The invention provides a method for constructing a surgical virtual operation teaching and training system. The method comprises the following concrete steps: (1) acquiring various inspection data classified according to normal people and patients, intensively storing the acquired data, and constructing an integrated male virtual human model and an integrated female virtual human model; (2) carrying out geometric modeling, computational modeling and deformation computation on medical data, and carrying out modeling on bones and soft tissues by adopting a multi-outline three-dimensional reconstruction algorithm; (3) reconstructing by adopting a three-dimensional model of 3DMAX10, mapping and giving physiological characteristics to organic tissues; (4) compiling related objects and simulated scenes of a virtual operation by virtual reality modeling language (VRML); (5) carrying out preoperative preparation in the virtual operation scenes, and checking and confirming patient information;(6) carrying out complete operational details of the actual method of the virtual operation again; (7) establishing a simulated operation teaching evaluation system; and (8) carrying out comprehensive evaluation and examination on a teacher and each trainee. In the method, the simulated operation teaching system is constructed by utilizing the virtual reality technology, thereby providing a wide and transparent simulated teaching and research platform for hospitals and medical schools.