S1P receptor modulators are administered following a dosage regimen providing a positive benefit-risk profile.

S1P receptor modulators are administered following a dosage regimen providing a positive benefit-risk profile.

A system for monitoring animal vitals can include a housing, a controller and one or more sensors for sensing vital signs. The housing can be configured to couple to one or more locations on an animal. A system can be adapted for monitoring two or more vital signs simultaneously and for conveying vital sign information to a user. A system can be adapted for alerting a user to the presence or absence of one or more conditions. A system can include a plurality of sensor units and can be adapted for monitoring a plurality of patients simultaneously.

A system for monitoring animal vitals can include a housing, a controller and one or more sensors for sensing vital signs. The housing can be configured to couple to one or more locations on an animal. A system can be adapted for monitoring two or more vital signs simultaneously and for conveying vital sign information to a user. A system can be adapted for alerting a user to the presence or absence of one or more conditions. A system can include a plurality of sensor units and can be adapted for monitoring a plurality of patients simultaneously.

Systems, methods, devices, and techniques for estimating a heart disease prediction of a mammal. An electrocardiogram (ECG) procedure is performed on a mammal, and a computer system obtains ECG data that describes results of the ECG over a period of time. The system provides a predictive input that is based on the ECG data to a predictive model, such as a neural network or other machine-learning model. In response, the predictive model processes the input to generate an estimated heart disease predictive characteristic of the mammal. The system outputs the estimated heart disease prediction of the mammal for presentation to a user.

A quantum spin liquid (QSL) electrophysiology device comprising a spontaneous and an induced quantum arrhythmia vacuum states, switchable between them through at least one entangled measurement of one negative differential resistance.

Disclosed are various examples and embodiments of systems, devices, components and methods configured to detect a location of a source of at least one cardiac rhythm disorder in a patient's heart. In some embodiments, electrogram signals are acquired from a patient's body surface, and subsequently normalized, adjusted and/or filtered, followed by generating a two-dimensional spatial map, grid or representation of the electrode positions, processing the amplitude-adjusted and filtered electrogram signals to generate a plurality of three-dimensional electrogram surfaces corresponding at least partially to the 2D map, one surface being generated for each or selected discrete times, and processing the plurality of three-dimensional electrogram surfaces through time to generate a velocity vector or other type of map using one or more of optical flow, video tracking analysis, motion capture analysis, motion estimation analysis, data association and segmentation tracking analysis, particle tracking analysis, and single-particle tracking analysis methods corresponding at least partially to the 2D map. Trained atrial discriminative machine learning models that facilitate the foregoing systems and methods, and that provide predictions or results concerning a patient's condition, are also disclosed.

A system for automatically assessing orthostatic hypotension for a patient supported on a patient support apparatus. The system receives position data identifying a first position of a patient supported on a patient support apparatus, and after a delay, receives vital signs data of the patient. The system receives position data identifying a second position of the patient supported on the patient support apparatus, and after a delay, receives vital signs data of the patient. The system determines an orthostatic hypotension assessment based on a difference in the vital signs data between the first and second positions. Based on the orthostatic hypotension assessment, the system modifies one or more conditions on the patient support apparatus to mitigate a risk for patient fall.

A system for automatically assessing orthostatic hypotension for a patient supported on a patient support apparatus. The system receives position data identifying a first position of a patient supported on a patient support apparatus, and after a delay, receives vital signs data of the patient. The system receives position data identifying a second position of the patient supported on the patient support apparatus, and after a delay, receives vital signs data of the patient. The system determines an orthostatic hypotension assessment based on a difference in the vital signs data between the first and second positions. Based on the orthostatic hypotension assessment, the system modifies one or more conditions on the patient support apparatus to mitigate a risk for patient fall.

A method for providing treatment recommendations for a patient to a physician is disclosed. The method includes receiving health information associated with the patient, determining a first risk score for the patient based on the health information using a trained predictor model, determining a second risk score for the patient based on the health information and at least one artificially closed care gap included in the health information using the predictor model, determining a predicted risk reduction score based on the first risk score and the second risk score, determining a patient classification based on the predicted risk reduction score, and outputting a report based on at least one of the first risk score, the second risk score, or the predicted risk reduction score.