Abstract: Systems and methods are disclosed for determining individual-specific blood flow characteristics. One method includes acquiring, for each of a plurality of individuals, individual-specific anatomic data and blood flow characteristics of at least part of the individual's vascular system; executing a machine learning algorithm on the individual-specific anatomic data and blood flow characteristics for each of the plurality of individuals; relating, based on the executed machine learning algorithm, each individual's individual-specific anatomic data to functional estimates of blood flow characteristics; acquiring, for an individual and individual-specific anatomic data of at least part of the individual's vascular system; and for at least one point in the individual's individual-specific anatomic data, determining a blood flow characteristic of the individual, using relations from the step of relating individual-specific anatomic data to functional estimates of blood flow characteristics.

Abstract: Systems and methods are disclosed for determining individual-specific blood flow characteristics. One method includes acquiring, for each of a plurality of individuals, individual-specific anatomic data and blood flow characteristics of at least part of the individual's vascular system; executing a machine learning algorithm on the individual-specific anatomic data and blood flow characteristics for each of the plurality of individuals; relating, based on the executed machine learning algorithm, each individual's individual-specific anatomic data to functional estimates of blood flow characteristics; acquiring, for an individual and individual-specific anatomic data of at least part of the individual's vascular system; and for at least one point in the individual's individual-specific anatomic data, determining a blood flow characteristic of the individual, using relations from the step of relating individual-specific anatomic data to functional estimates of blood flow characteristics.

Abstract: The invention relates to a module housing made of plastic, in particular a thermosetting polymer, with an embedded cooling element and at least one screw sleeve, which has a collar with an exposed mounting surface with which the module housing can be mounted on a support functioning as an external heat sink. The cooling element and the at least one screw sleeve form a monolithic element with which heat can be conducted from the cooling element to the support via at least the mounting surface.

Abstract: Systems and methods for estimating the post-treatment ultrafiltration rate of a patient are provided. A medical device can be configured to determine an estimated post-treatment ultrafiltration rate based on one or more values associated with a patient prepared to undergo treatment with the medical device. The medical device can also be configured to compare the estimated post-treatment ultrafiltration rate with one or more threshold values. The medical device can be configured to have an alert module, which can be activated when the estimated post-treatment ultrafiltration rate exceeds the one or more threshold values.

Abstract: Systems, media, methods, and kits disclosed herein can improve analysis capabilities of genomic materials. Results from such analyses can be used to detect genomic biomarkers in one or more genomic materials. The systems, media, methods and kits disclosed herein can identify changes or patterns among samples, and can employ machine learning methods to explore changes or potential changes in biological conditions or risks thereof. Further, the systems, media, methods and kits disclosed herein can utilize machine learning algorithms to analyze samples with high accuracy.

Abstract: The invention relates to a module housing made of plastic, in particular a thermosetting polymer, with an embedded cooling element and at least one screw sleeve, which has a collar with an exposed mounting surface with which the module housing can be mounted on a support functioning as an external heat sink. The cooling element and the at least one screw sleeve form a monolithic element with which heat can be conducted from the cooling element to the support via at least the mounting surface.

Abstract: Systems and methods are disclosed for determining individual-specific blood flow characteristics. One method includes acquiring, for each of a plurality of individuals, individual-specific anatomic data and blood flow characteristics of at least part of the individual's vascular system; executing a machine learning algorithm on the individual-specific anatomic data and blood flow characteristics for each of the plurality of individuals; relating, based on the executed machine learning algorithm, each individual's individual-specific anatomic data to functional estimates of blood flow characteristics; acquiring, for an individual and individual-specific anatomic data of at least part of the individual's vascular system; and for at least one point in the individual's individual-specific anatomic data, determining a blood flow characteristic of the individual, using relations from the step of relating individual-specific anatomic data to functional estimates of blood flow characteristics.

Abstract: Systems and methods are disclosed for determining individual-specific blood flow characteristics. One method includes acquiring, for each of a plurality of individuals, individual-specific anatomic data and blood flow characteristics of at least part of the individual's vascular system; executing a machine learning algorithm on the individual-specific anatomic data and blood flow characteristics for each of the plurality of individuals; relating, based on the executed machine learning algorithm, each individual's individual-specific anatomic data to functional estimates of blood flow characteristics; acquiring, for an individual and individual-specific anatomic data of at least part of the individual's vascular system; and for at least one point in the individual's individual-specific anatomic data, determining a blood flow characteristic of the individual, using relations from the step of relating individual-specific anatomic data to functional estimates of blood flow characteristics.

Abstract: Systems and methods are disclosed for estimating patient-specific blood flow characteristics. One method includes acquiring, for each of a plurality of individuals, a geometric model and estimated blood flow characteristics of at least part of the individual's vascular system; executing a machine learning algorithm on the geometric model and estimated blood flow characteristics for each of the plurality of individuals; identifying, using the machine learning algorithm, features predictive of blood flow characteristics corresponding to a plurality of points in the geometric models; acquiring, for a patient, a geometric model of at least part of the patient's vascular system; and using the identified features to produce estimates of the patient's blood flow characteristic for each of a plurality of points in the patient's geometric model.

Abstract: Systems and methods for estimating the post-treatment ultrafiltration rate of a patient are provided. A medical device can be configured to determine an estimated post-treatment ultrafiltration rate based on one or more values associated with a patient prepared to undergo treatment with the medical device. The medical device can also be configured to compare the estimated post-treatment ultrafiltration rate with one or more threshold values. The medical device can be configured to have an alert module, which can be activated when the estimated post-treatment ultrafiltration rate exceeds the one or more threshold values.

Abstract: Systems and methods are disclosed for determining individual-specific blood flow characteristics. One method includes acquiring, for each of a plurality of individuals, individual-specific anatomic data and blood flow characteristics of at least part of the individual's vascular system; executing a machine learning algorithm on the individual-specific anatomic data and blood flow characteristics for each of the plurality of individuals; relating, based on the executed machine learning algorithm, each individual's individual-specific anatomic data to functional estimates of blood flow characteristics; acquiring, for an individual and individual-specific anatomic data of at least part of the individual's vascular system; and for at least one point in the individual's individual-specific anatomic data, determining a blood flow characteristic of the individual, using relations from the step of relating individual-specific anatomic data to functional estimates of blood flow characteristics.

Abstract: Systems and methods for estimating the post-treatment ultrafiltration rate of a patient are provided. A medical device can be configured to determine an estimated post-treatment ultrafiltration rate based on one or more values associated with a patient prepared to undergo treatment with the medical device. The medical device can also be configured to compare the estimated post-treatment ultrafiltration rate with one or more threshold values. The medical device can be configured to have an alert module, which can be activated when the estimated post-treatment ultrafiltration rate exceeds the one or more threshold values.

Abstract: Systems and methods are disclosed for determining individual-specific blood flow characteristics. One method includes acquiring, for each of a plurality of individuals, individual-specific anatomic data and blood flow characteristics of at least part of the individual's vascular system; executing a machine learning algorithm on the individual-specific anatomic data and blood flow characteristics for each of the plurality of individuals; relating, based on the executed machine learning algorithm, each individual's individual-specific anatomic data to functional estimates of blood flow characteristics; acquiring, for an individual and individual-specific anatomic data of at least part of the individual's vascular system; and for at least one point in the individual's individual-specific anatomic data, determining a blood flow characteristic of the individual, using relations from the step of relating individual-specific anatomic data to functional estimates of blood flow characteristics.

Abstract: Systems, media, methods, and kits disclosed herein can improve analysis capabilities of genomic materials. Results from such analyses can be used to detect genomic biomarkers in one or more genomic materials. The systems, media, methods and kits disclosed herein can identify changes or patterns among samples, and can employ machine learning methods to explore changes or potential changes in biological conditions or risks thereof. Further, the systems, media, methods and kits disclosed herein can utilize machine learning algorithms to analyze samples with high accuracy.

Abstract: Systems and methods are disclosed for determining individual-specific blood flow characteristics. One method includes acquiring, for each of a plurality of individuals, individual-specific anatomic data and blood flow characteristics of at least part of the individual's vascular system; executing a machine learning algorithm on the individual-specific anatomic data and blood flow characteristics for each of the plurality of individuals; relating, based on the executed machine learning algorithm, each individual's individual-specific anatomic data to functional estimates of blood flow characteristics; acquiring, for an individual and individual-specific anatomic data of at least part of the individual's vascular system; and for at least one point in the individual's individual-specific anatomic data, determining a blood flow characteristic of the individual, using relations from the step of relating individual-specific anatomic data to functional estimates of blood flow characteristics.

Abstract: Systems and methods for estimating the post-treatment ultrafiltration rate of a patient are provided. A medical device can be configured to determine an estimated post-treatment ultrafiltration rate based on one or more values associated with a patient prepared to undergo treatment with the medical device. The medical device can also be configured to compare the estimated post-treatment ultrafiltration rate with one or more threshold values. The medical device can be configured to have an alert module, which can be activated when the estimated post-treatment ultrafiltration rate exceeds the one or more threshold values.

Abstract: A system for noninvasively determining at least one physiological characteristic of a patient may include at least one computer system configured to, using a three-dimensional surface mesh model created using patient-specific imaging data, create a three-dimensional combined surface and volume mesh model, including at least a first model portion that has a different spatial resolution than at least a second model portion. The computer system may be further configured to input the three-dimensional surface and volume mesh model into a fluid simulation system and determine a measurement of the physiological characteristic, using the fluid simulation system.

Abstract: A system for noninvasively determining at least one physiological characteristic of a patient may include at least one computer system configured to, using a three-dimensional surface mesh model created using patient-specific imaging data, create a three-dimensional combined surface and volume mesh model, including at least a first model portion that has a different spatial resolution than at least a second model portion. The computer system may be further configured to input the three-dimensional surface and volume mesh model into a fluid simulation system and determine a measurement of the physiological characteristic, using the fluid simulation system.

Abstract: Systems and methods are disclosed for determining individual-specific blood flow characteristics. One method includes acquiring, for each of a plurality of individuals, individual-specific anatomic data and blood flow characteristics of at least part of the individual's vascular system; executing a machine learning algorithm on the individual-specific anatomic data and blood flow characteristics for each of the plurality of individuals; relating, based on the executed machine learning algorithm, each individual's individual-specific anatomic data to functional estimates of blood flow characteristics; acquiring, for an individual and individual-specific anatomic data of at least part of the individual's vascular system; and for at least one point in the individual's individual-specific anatomic data, determining a blood flow characteristic of the individual, using relations from the step of relating individual-specific anatomic data to functional estimates of blood flow characteristics.

Abstract: Systems and methods are disclosed for determining individual-specific blood flow characteristics. One method includes acquiring, for each of a plurality of individuals, individual-specific anatomic data and blood flow characteristics of at least part of the individual's vascular system; executing a machine learning algorithm on the individual-specific anatomic data and blood flow characteristics for each of the plurality of individuals; relating, based on the executed machine learning algorithm, each individual's individual-specific anatomic data to functional estimates of blood flow characteristics; acquiring, for an individual and individual-specific anatomic data of at least part of the individual's vascular system; and for at least one point in the individual's individual-specific anatomic data, determining a blood flow characteristic of the individual, using relations from the step of relating individual-specific anatomic data to functional estimates of blood flow characteristics.