Abstract: Particle or hadron therapy is used on abnormal tissue using carbon atoms, protons, or helium atoms run through a linear accelerator and then directed at the target in the body. This can be used to treat, for example, atrial fibrillation, ventricular tachycardia, hypertension, seizures, gastrointestinal maladies, etc. Contouring and gating may be used to account for cardiac and respiratory motion, helping reduce collateral damage.

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: Particle or hadron therapy is used on abnormal tissue using carbon atoms, protons, or helium atoms run through a linear accelerator and then directed at the target in the body. This can be used to treat, for example, atrial fibrillation, ventricular tachycardia, hypertension, seizures, gastrointestinal maladies, etc. Contouring and gating may be used to account for cardiac and respiratory motion, helping reduce collateral damage.

Abstract: Methods, systems, and media are disclosed for reconstructing bioelectronic lead placement. In some embodiments, the disclosed system can include a processor configured to determine relationships between EP signals of one or more pairs of a plurality of electrodes over one or more sampling time periods, wherein the plurality electrodes are separately placed on a patient's body for collecting the EP signals, and to reconstruct geometry of the plurality of electrodes based on the relationships between the EP signals.

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: The present disclosure relates generally to electroporation systems and utilizing algorithms for electroporation pulse delivery including a patient's EKG/EGM monitoring. In some embodiments, an electroporation delivery system may include an electrocardiogram operatively connected to a processing device and a memory. One or more sensors may be operatively connected to the electrocardiogram for measuring electrical activity QRS complex of a patient's heart. One or more electrodes for treatment may be disposed in, at, or near the patient's heart, the one or more electrodes operatively connected to a pulse delivery mechanism. The electroporation delivery system may be configured to determine whether an electroporation pulse is deliverable to a patient based on the electrocardiogram.

Abstract: Embodiments of the present disclosure relate to treating diseased tissue with ablation therapy. In an embodiment, an apparatus comprises a catheter having an elongate body extending between a proximal end and a distal end. The apparatus further includes a balloon structure arranged proximal to the distal end of the catheter, wherein the balloon structure has a first portion with a first permeability and a second portion with a second permeability such that the first permeability is different than the second permeability. In addition, the apparatus includes a first electrode arranged on or within the balloon structure and configured to: transmit current through the first portion, receive current transmitted through the first portion or both.

Abstract: The present disclosure relates generally to electroporation systems and utilizing algorithms for electroporation pulse delivery including a patient's EKG/EGM monitoring. In some embodiments, an electroporation delivery system may include an electrocardiogram operatively connected to a processing device and a memory. One or more sensors may be operatively connected to the electrocardiogram for measuring electrical activity QRS complex of a patient's heart. One or more electrodes for treatment may be disposed in, at, or near the patient's heart, the one or more electrodes operatively connected to a pulse delivery mechanism. The electroporation delivery system may be configured to determine whether an electroporation pulse is deliverable to a patient based on the electrocardiogram.

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: 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: Methods, systems, and media are disclosed for detrending a bioelectric signal. In some embodiments, the disclosed system can include a processor configured to receive the bioelectric signal, identify at least one breakpoint section corresponds to a rapid change of amplitude of the bioelectric signal, smooth an amplitude of the bioelectric signal after the at least one breakpoint section; and reconstruct the bioelectric signal based on the smoothed amplitude of the bioelectric signal and a reset of the breakpoint section to remove extrinsic components caused by a non-biological factor from the bioelectric signal.

Abstract: Systems and methods for assessing the condition of a heart of an individual. A system obtains electrocardiogram (ECG) data that describes a result of an ECG of the individual. The ECG data can be provided to a machine-learning model, which processes the data and generates an output indicative of the condition of the heart. The output relates to a level of troponin in a bloodstream of the individual. The system can then provide the output of the machine-learning model to a post-processing resource.

Abstract: Systems, methods, devices, and other techniques for estimating the age and sex of a person through analysis of an electrocardiogram (ECG) recording for the person. Some aspects include recording an ECG of a person, processing data representing the ECG with an age-estimation neural network to generate an estimated age of the person, and outputting an indication of the estimated age of the person. Other aspects include processing the ECG with a sex prediction neural network to generate a predicted sex of the person and outputting an indication of the predicted sex of the person.

Abstract: Methods, systems, and media are disclosed for reconstructing bioelectronic lead placement. In some embodiments, the disclosed system can include a processor configured to determine relationships between EP signals of one or more pairs of a plurality of electrodes over one or more sampling time periods, wherein the plurality electrodes are separately placed on a patient's body for collecting the EP signals, and to reconstruct geometry of the plurality of electrodes based on the relationships between the EP signals.

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: Various aspects of the present disclosure are directed toward apparatuses, systems, and methods for applying ablation therapy to a tissue region. The apparatuses, systems, and methods may include a balloon structure and one or more electrodes arranged on or within the balloon structure and configured to deliver energy to the tissue region.

Abstract: Particle or hadron therapy is used on abnormal tissue using carbon atoms, protons, or helium atoms run through a linear accelerator and then directed at the target in the body. This can be used to treat, for example, atrial fibrillation, ventricular tachycardia, hypertension, seizures, gastrointestinal maladies, etc. Contouring and gating may be used to account for cardiac and respiratory motion, helping reduce collateral damage.

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: In various aspects, the present disclosure provides methods for applying ablation therapy to a target tissue region within a patient, which methods include: (a) navigating a catheter to a target tissue region within the patient, the catheter including an elongate body having a proximal portion and a distal portion and a balloon structure positioned at the distal portion of the elongate body, which balloon structure may be permeable to a calcium-ion-containing solution that comprises one or more calcium salts; (b) positioning the balloon structure at the target tissue region; (c) delivering energy to the target tissue region; and (d) eluting the calcium-ion-containing solution from the balloon structure before, during, and/or after delivering the energy to the target tissue region. In various other aspects, the present disclosure provides apparatuses that can be used for performing such methods, among others.

Abstract: Various aspects of the present disclosure are directed toward apparatuses, systems, and methods for assessing electroporation therapy applied to a tissue region of a patient. In certain instances, the apparatuses, systems, and methods may include one or more sensors configured to sense an application of electroporation energy by an electroporation device to determine a location of the electroporation device within the patient.