Abstract: This document describes methods and materials for the treatment of pathological conditions, including arrhythmias and trauma, using temperature modulation via implantable devices. For example, this document relates to methods and devices for treating atrial and/or ventricular fibrillation by cooling the epicardium.

Abstract: A system obtains a maternal electrocardiogram (ECG) signal that represents an ECG of a pregnant mother during a first time interval. The system further obtains a mixed maternal-fetal ECG signal that represents a combined ECG of the mother and her fetus during the first time interval; processes the maternal ECG signal and the mixed maternal-fetal ECG signal to generate a fetal ECG signal that represents the ECG of the fetus during the time interval, the fetal ECG signal substantially excluding the maternal ECG signal; and provides an output based on the fetal ECG signal.

Abstract: This document describes methods and devices for securing epicardial devices. For example, this document describes methods and devices for securing epicardial devices by passing a sheath into a pericardial space of a patient through a first percutaneous access site, passing a guidewire through the sheath into the pericardial space of the patient, passing the guidewire through a transverse sinus of the patient, passing a snare device into the pericardial space through a second percutaneous access site, and capturing a free end portion of the guidewire using the snare device.

Abstract: Provided herein are methods, systems, and computer program products for the detection and evaluation of cardiac condition in a lead-invariant manner.

Abstract: Devices and methods are provided for the treatment of pathological conditions including arrhythmias and trauma using temperature modulation via implantable or worn devices. For example, in one example embodiment this document relates to devices and methods for treating atrial or ventricular fibrillation by cooling the epicardium. The devices and methods can also be used to treat other disorders by applying heating and/or cooling to a patient in a number of different manners.

Abstract: 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.

Abstract: 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.

Abstract: Devices and methods for the treatment of heart conditions, and other medical purposes, include cardiac pacing systems. For example, this document describes temporary transvenous endocardial pacemaker systems and devices for deploying such systems without the need for conventional imaging procedures.

Abstract: Provided herein are methods, systems, and computer program products for the detection and evaluation of cardiac condition in a lead-invariant manner.

Abstract: The present disclosure provides methods and systems for displaying a user interface that presents a classifier statistic, mathematical equation output, or ROC curve on a computing device or mobile phone or tablet. The method comprises: receiving a user's input on said screen using a cursor or pointing element whereby user input comprises selection of a point along a plotted curve, ROC curve, or mathematical function so that input results in displaying one or more figures corresponding to the select statistics or threshold term defined by the user input.

Abstract: In some aspects, values of features obtained from training first and second machine-learning models are analyzed to correlate at least a subset of features from the first machine-learning model with at least a subset of features from the second machine-learning model. The correlated features are then applied to update the first or second machine-learning model, or to train a third machine-learning model. In other aspects, a generator machine-learning model processes a seed and a target characteristic indicator to generate a synthetic ECG signal. The synthetic ECG signal is biased according to a target physiological characteristic represented by the target characteristic indicator. The generator machine-learning model can be trained using an expert machine-learning model and in an adversarial process with a discriminator machine-learning model.

Abstract: Apparatuses and methods are provided to predict or diagnose an ischemic event, such as a stroke or a transient ischemic attack (TIA). A machine-learning model such as a neural network is generated that allows for recognition of an ECG consistent with an ischemic event. A system is trained and used to process a recording of ECG data from a patient to generate a prediction indicating a likelihood that the patient will experience a stroke. In other examples, a system is trained and used to process a recording of ECG data from a patient and detect an ischemic event for the patient who did not appear to have such an ischemic event.

Abstract: Systems, methods, devices, and other techniques for processing an ECG recording to assess a condition of a mammal. Assessing the condition of the mammal can include screening for atrial fibrillation, and screening for atrial fibrillation can include obtaining a first neural network input, the first neural network input representing an electrocardiogram (ECG) recording of the mammal, and processing the first neural network input with a neural network to generate an atrial fibrillation prediction for the mammal.

Abstract: An apparatus and method for detecting a level of cardiovascular disease. The apparatus includes at least a processor and a memory communicatively connected to the at least a processor, wherein the memory contains instructions configuring the at least a processor to: receive a plurality of voltage-time data, generate at least a feature vector from the voltage-time data by at least a feature model, input the at least feature vector into a cardiovascular classification model, generate at least a disease indication in a subject using the classification model, wherein the disease indication comprises a level of myocarditis, and display the at least a disease indication.

Abstract: Systems, methods, devices, and techniques for estimating an ejection-fraction characteristic 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 an ejection-fraction predictive model, such as a neural network or other machine-learning model. In response, the ejection-fraction predictive model processes the input to generate an estimated ejection-fraction characteristic of the mammal. The system outputs the estimated ejection-fraction characteristic of the mammal for presentation to a user.

Abstract: 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.

Abstract: This document provides devices and methods for monitoring health patient parameters using a wearable monitoring device. For example, this document provides monitoring devices with multiple sensors, multiple types of sensors, algorithms for managing the multiple sensors to enhance monitor performance, and for detection of health events using health parameter data that is acquired by the monitoring system.

Abstract: Provided herein are methods, systems, and computer program products for the detection and evaluation of cardiac condition in a lead-invariant manner.

Abstract: A method includes ingesting, by a clinical trial management platform, data from multiple clinical trial site systems associated with multiple clinical trials, responsive to authentication of user credentials of a user, providing the user with access to the clinical trial management platform, based on the user credentials, identifying a particular clinical trial associated with the user, through the clinical trial management platform, providing the user with access to multiple clinical trial software services based on the authenticated user credentials, based on the ingested data for the particular clinical trial associated with the user, presenting to the user a user-specific task list for user tasks related to the particular clinical trial; and through the clinical trial management platform, establishing a communication link between the user and another user, the communication link enabling direct, real-time messaging via the clinical trial management platform between the user and the other user.

Abstract: Systems, methods, devices, and other techniques for processing an ECG recording to assess a condition of a mammal. Assessing the condition of the mammal can include screening for atrial fibrillation, and screening for atrial fibrillation can include obtaining a first neural network input, the first neural network input representing an electrocardiogram (ECG) recording of the mammal, and processing the first neural network input with a neural network to generate an atrial fibrillation prediction for the mammal.