Abstract: A system is described for generating a revascularization score for a blockage of a coronary artery in a heart. The system accesses indications of viability of myocardial tissue in the heart, a blockage state of the blockage that includes a blockage location and a blockage amount, and the perfusion territory of the myocardial tissue. Based on the myocardial tissue state, blockage state, and perfusion territory, the system generates a revascularization score for the blockage. The system generates a graphic of the heart that illustrates coronary arteries, myocardial tissue state, blockage state, and the revascularization score. The system displays the graphic to provide a visual representation of the revascularization score for the blockage of the coronary artery.

Abstract: A system is described for generating a revascularization score for a blockage of a coronary artery in a heart. The system accesses indications of viability of myocardial tissue in the heart, a blockage state of the blockage that includes a blockage location and a blockage amount, and the perfusion territory of the myocardial tissue. Based on the myocardial tissue state, blockage state, and perfusion territory, the system generates a revascularization score for the blockage. The system generates a graphic of the heart that illustrates coronary arteries, myocardial tissue state, blockage state, and the revascularization score. The system displays the graphic to provide a visual representation of the revascularization score for the blockage of the coronary artery.

Abstract: A system is provided for generating an ablation plan for an ablation procedure to be performed on a body part of a patient having an abnormal pattern of electrical activity. The system receives patient data that includes a patient cardiogram, a patient body part image; and patient health data. The system employs an ablation target system to identify an ablation target within the body part based on at least some of the patient data. The system also employs an ablation plan system to identify, based on at least some of the patient data and the ablation target, an ablation plan that includes target parameter values for ablation device parameters for controlling an ablation device. The ablation plan system is developed based on data that includes data sets with patient data associated with an ablation plan. The system then outputs an indication of the ablation target and the ablation plan.

Abstract: Systems are provided for synthesizing leads of an electrocardiogram (ECG) based on a subject ECG collected from a subject and converting a nonstandard ECG based on a nonstandard placement of electrodes to a standard ECG with a standard placement of electrodes. The described systems may generate simulated ECGs based on simulations of electrical activity of hearts having different heart configurations. From each simulation, simulated ECGs are generated assuming a specification of electrode position(s) for each lead of an ECG. The systems identify a simulated ECG that is similar to the subject ECG. Based on the simulation from which that simulated ECG was generated, the systems identify a synthesized ECG or converted ECG.

Abstract: A system is provided for generating an ablation plan for an ablation procedure to be performed on a body part of a patient having an abnormal pattern of electrical activity. The system receives patient data that includes a patient cardiogram, a patient body part image; and patient health data. The system employs an ablation target system to identify an ablation target within the body part based on at least some of the patient data. The system also employs an ablation plan system to identify, based on at least some of the patient data and the ablation target, an ablation plan that includes target parameter values for ablation device parameters for controlling an ablation device. The ablation plan system is developed based on data that includes data sets with patient data associated with an ablation plan. The system then outputs an indication of the ablation target and the ablation plan.

Abstract: A system is provided that employs a machine learning (ML) decision tree to provide a treatment analysis for an arrhythmia. The ML decision tree includes decision nodes (non-leaf nodes) and treatment analysis nodes (leaf nodes). Each decision node corresponds to a feature derived from electronic health records and has branches corresponding to feature values. A treatment analysis node corresponds to a treatment analysis based on feature values of a path from the root node to that treatment analysis node. To provide a treatment analysis for a candidate, the system identifies a path from the root node to a treatment analysis node based on a candidate feature vector derived from an electronic health record of the candidate and outputs the treatment analysis of the treatment analysis node of the identified path.

Abstract: A system for guiding implantation of an energy delivery component of a cardiac pacing device at a fixation location within a heart of a patient is provided. During a procedure to implant an energy pulse delivery component, the system receives a patient cardiogram collected during pacing of the energy pulse delivery component while the energy pulse delivery component is positioned at a current location within the heart. The system then determines based on the patient cardiogram the current location of the energy pulse delivery component. The system then outputs an indication of the current location to guide affixing of the energy pulse delivery component at the intended fixation location. This process is repeated until the energy pulse delivery component is at the fixation location. The system also evaluates the effectiveness of pacing at intermediate location to optimize the final location based upon simulated electro-mechanics of the system in near-real time.

Abstract: A system is provided for augmenting a three-dimensional (3D) model of a heart to indicate the tissue state. The system accesses a 3D model of a heart, accesses two-dimensional (2D) images of tissue state slices of the heart, and accesses source location information of an arrhythmia. The system augments the 3D model with an indication of a source location based on the source location information. For each of a plurality of the tissue state slices of the heart, the system augments a 3D model slice of the 3D model that corresponds to that tissue state slice with an indication of the tissue state of the heart represented by the tissue state information of that tissue state slice. The system then displays a representation of the 3D model that indicates the source location of the arrhythmia and the tissue state of the heart.

Abstract: A system for generating an encoding of a lead of electrocardiogram (ECG) represented as an ECG image. The system identifies a reference pulse of the ECG image having a reference width pixel count, a reference height pixel count, a reference time, and a reference voltage. The system identifies a baseline pixel-row of a plotline of the ECG image that contains a graph of the lead. The system encodes per-pixel timing information based on the reference time and the reference width pixel count. The system, for a plurality of pixel-columns, identifies a voltage pixel-row of that pixel-column that has an ECG value of the graph and encodes a voltage based on distance between the baseline pixel-row and the voltage pixel-row and based on the reference voltage and the reference height pixel count.

Abstract: A system is provided for augmenting a three-dimensional (3D) model of a heart to indicate the tissue state. The system accesses a 3D model of a heart, accesses two-dimensional (2D) images of tissue state slices of the heart, and accesses source location information of an arrhythmia. The system augments the 3D model with an indication of a source location based on the source location information. For each of a plurality of the tissue state slices of the heart, the system augments a 3D model slice of the 3D model that corresponds to that tissue state slice with an indication of the tissue state of the heart represented by the tissue state information of that tissue state slice. The system then displays a representation of the 3D model that indicates the source location of the arrhythmia and the tissue state of the heart.

Abstract: A system is provided for augmenting a three-dimensional (3D) model of a heart to indicate the tissue state. The system accesses a 3D model of a heart, accesses two-dimensional (2D) images of tissue state slices of the heart, and accesses source location information of an arrhythmia. The system augments the 3D model with an indication of a source location based on the source location information. For each of a plurality of the tissue state slices of the heart, the system augments a 3D model slice of the 3D model that corresponds to that tissue state slice with an indication of the tissue state of the heart represented by the tissue state information of that tissue state slice. The system then displays a representation of the 3D model that indicates the source location of the arrhythmia and the tissue state of the heart.

Abstract: Methods and systems for analyzing and treating digestive disorders (including gastrointestinal disorders) are provided. A system provides various technologies (e.g., machine learning and simulations) to support such analysis and treatment of digestive disorders. The system may employ computational modeling of the digestive system based on anatomical characteristics and electrical characteristics of the digestive system to simulate motion and electrical activity. The system generates representations of the electrical activity such as an electrogastrogram and generates mappings of the representations to characteristic values of the simulations. The system may train a machine learning model based on the mappings. When treating a patient, the mappings and/or the machine learning model may be employed to identify a patient characteristic based on a patient representation of electrical activity collected from the patient.

Abstract: A method is provided for treating a patient with an arrhythmia. In some embodiments, the method collects a first patient arrhythmia cardiogram from the patient. The method identifies a first target location and a first ablation pattern associated with a first library arrhythmia cardiogram that is similar to the first patient arrhythmia cardiogram. The method then performs a first ablation near the first target location, factoring in the first ablation pattern, and after the ablation, collects a second patient arrhythmia cardiogram of the patient. The method continues to identify a second target location and a second ablation pattern associated with a second library arrhythmia cardiogram that is similar to the second patient arrhythmia cardiogram. The second library arrhythmia cardiogram is identified, in part, based on ablation characteristics of the first ablation. The method then performs a second ablation near the second target location, factoring in the second ablation pattern.

Abstract: A system for guiding implantation of an energy delivery component of a cardiac pacing device at a fixation location within a heart of a patient is provided. During a procedure to implant an energy pulse delivery component, the system receives a patient cardiogram collected during pacing of the energy pulse delivery component while the energy pulse delivery component is positioned at a current location within the heart. The system then determines based on the patient cardiogram the current location of the energy pulse delivery component. The system then outputs an indication of the current location to guide affixing of the energy pulse delivery component at the intended fixation location. This process is repeated until the energy pulse delivery component is at the fixation location. The system also evaluates the effectiveness of pacing at intermediate location to optimize the final location based upon simulated electro-mechanics of the system in near-real time.