Systems, methods, electronic devices and computer-readable media for charting dental information are described. The method includes generating or retrieving a dental data set including separately-modifiable parameters defining dental information relative to a base parametric model, the parameters providing information for generating signals for displaying a three-dimensional (3D) representation of at least a portion of a dentition represented by the dental data set; receiving an input via the 3D representation; and based on the received input, adjusting at least one of the parameters.

A mechanical ventilator (10) is connected with a ventilated patient (12) to provide ventilation in accordance with ventilator settings of the mechanical ventilator. Physiological values (variables) are acquired for the ventilated patient using physiological sensors (32). A ventilated patient cardiopulmonary (CP) model (40) is fitted to the acquired physiological variables values to generate a fitted ventilated patient CP model by fine-tuning its parameters (50). Updated ventilator settings are determined by adjusting model ventilator settings of the fitted ventilated patient CP model to minimize a cost function (60). The updated ventilator settings may be displayed on a display component (22) as recommended ventilator settings for the ventilated patient, or the ventilator settings of the mechanical ventilator may be automatically changed to the updated ventilator settings so as to automatically control the mechanical ventilator.

The present invention relates to a decision support system (DSS), a medical monitoring system (100), and a corresponding method for identifying the need for measurement of cardiac output (CO) based on one or more comparisons (COMP1, COMP2) in a physiological model. More specifically, for identifying when an approximated value of CO cannot be correct due to circulatory compromise and as such that another estimated or measured value of CO is required.

Various implementations of methods and systems for computing a patient-specific medical report associated with a diagnosis and generating supporting documentation for the report are described in this disclosure. In some implementations, the medical documentation system can assist doctors in providing care to hospitalized patients. In some implementations, the medical documentation system can generate a patient-specific appeal letter in response to a medical claim denial. Results of patient data input into evidence-based models can be presented to a user thorough a graphical user interface (GUI), which can also allow the user to interact with the medical documentation system. In some implementations, the medical documentation system can generate an interactive graphical user interface (GUI) that can be used to analyze patient data.

Contemplated systems and methods allow for prediction of chemotherapy outcome for patients diagnosed with high-grade bladder cancer. In particularly preferred aspects, the prediction is performed using a model based on machine learning wherein the model has a minimum predetermined accuracy gain and wherein a thusly identified model provides the identity and weight factors for omics data used in the outcome prediction.

Systems and methods are provided for segmenting tissue within a computed tomography (CT) scan of a region of interest into one of a plurality of tissue classes. A plurality of atlases are registered to the CT scan to produce a plurality of registered atlases. A context model representing respective likelihoods that each voxel of the CT scan is a member of each of the plurality of tissue classes is determined from the CT scan and a set of associated training data. A proper subset of the plurality of registered at lases is selected according to the context model and the registered atlases. The selected proper subset of registered atlases are fused to produce a combined segmentation.

An analysis system, which includes a processor and a memory connected with the processor, further includes: a model applying unit that predicts at least one change among changes between the conditions of target persons in the case of an intervention not being followed and the conditions of the target persons in the case of the intervention being followed with reference to the health checkup information, the medical information, and the clinical condition transition models; and a simulation unit that predicts medical care expenses using the conditions predicted by the model applying unit, and calculates the medical care expense of a group to which the target persons belong by aggregating the predicted medical care expenses of the individual target persons. In addition the simulation unit outputs screen data used for displaying the calculated medical care expense of the group.

The invention describes a method for identifying alterations in a musculoskeletal system of a subject, wherein the method comprises the steps of associating, with the subject, detecting means capable of detecting physical quantities representative of a state of the subject, detecting the physical quantities through the detecting means, identifying a biomechanical model for the subject, determining combined movements of muscles and bones as a function of said physical quantities detected and of said identified biomechanical model, converting the combined movements into a plurality of movement steps of segments and joints, computing parameters representative of the alterations, comparing the parameters computed with predefined reference values representative of alteration thresholds in the musculoskeletal system, identifying the alterations as a function of a failed matching between the computed parameters and the predefined reference values, and determining the belonging of this correspondence to one or more groups of musculoskeletal pathologies as a function of said identified alteration.

The invention further comprises a system for identifying alterations in a musculoskeletal system of a subject.

The invention relates to the system and method of remote ECG monitoring, remote disease screening, and early-warning system based on wavelet analysis. The system includes a wireless ECG signal acquisition device, a mobile terminal, and a cloud storage platform. The wireless ECG signal acquisition device worn on the user's chest is used to collect ECG signals anywhere and anytime. The method includes transmitting the ECG signals to the mobile terminal using the wavelet analysis algorithm, analyzing and processing the received ECG signal, and uploading the processed ECG signals to the cloud storage platform. The cloud storage platform stores users' personal information and ECG signals. According to the ECG features detection with support vector machine learning algorithm for heart diseases diagnosis and features classification, the system gives feedback report and proposal, and transmits them to the mobile terminal.

Systems and methods for evaluating ND are described herein. An example method can include constructing a non-sequential (NSC) ray-tracing model of an eye with an ophthalmic lens, and modelling a light source and a detector. The detector can be configured to mimic a retina of the eye. The method can also include computing irradiance data using the light source, the NSC ray-tracing model, and the detector. Irradiance data can be computed for each of a plurality of pupil sizes. The method can further include evaluating ND by analyzing the respective irradiance data for each of the pupil sizes. Also described herein are methods for designing an ophthalmic lens edge that reduces the incidence of ND for a given ophthalmic lens by adjusting the edge thickness and/or the scatter.