Disclosed are various embodiments for integrated diffuse correlation spectroscopy. A first control signal can be sent to a switch to cause an integrator to integrate a current from a photodiode. An integrated current can be received from the integrator, and a data signal can be sent to a computing device based at least in part on the integrated current. A second control signal can be sent to a switch to cause the integrator to cease integrating the current from the photodiode.

A catheter-based device for determining the radial expansion force required to displace an occlusion in a vessel located in a subject. The device comprises an elongate body defining proximal and distal termini. The body comprises a sheath that encloses a hollow lumen within, which extends along substantially the full length of the body. The proximal terminal region of the body comprises: a user-interfacing hub, the hub comprising a handle for maneuvering the body and configured for handling by an operator; a control interface for controlling the device; and a sensor configured to measure one or more parameters relevant to a force applied to the vessel by the device. The distal terminal region of the body comprises an expandable member movable between a retracted position, in which the expandable member is within the hollow lumen, and a deployed position, in which the expandable member is disposed beyond the distal terminus, and controllable via the control interface to expand radially. The expansion of the expandable member is correlated to a defined radial expansion force value.

A method includes: receiving first data including physiological information obtained from a subject and a first result that a disease is developing; specifying a first time point at which the physiological information included in the first data is obtained; receiving second data including the physiological information obtained from the subject and a second result that the disease is not developing; specifying a second time point at which the physiological information included in the second data is obtained; upon determining that a time interval between the first time point and the second time point is smaller than a first predetermined value, assigning, to the second data, a first training label indicating that the disease is developing and a weighting index that is capable of taking a plurality of values according to the time interval; and performing machine learning of a model by using the second data as training data.

A method includes: receiving first data including physiological information obtained from a subject and a first result that a disease is developing; specifying a first time point at which the physiological information included in the first data is obtained; receiving second data including the physiological information obtained from the subject and a second result that the disease is not developing; specifying a second time point at which the physiological information included in the second data is obtained; upon determining that a time interval between the first time point and the second time point is smaller than a first predetermined value, assigning, to the second data, a first training label indicating that the disease is developing and a weighting index that is capable of taking a plurality of values according to the time interval; and performing machine learning of a model by using the second data as training data.

A pulse oximeter includes a light emitting device that emits a first light and a second light, a light detecting device that outputs a first signal and a second signal respectively corresponding to an intensity of the first light and an intensity of the second light after interacting with a tissue of a subject, a processing device that calculates a pulsation rate of at least one of the first signal and the second signal, calculates a percutaneous arterial oxygen saturation of the subject, and estimates a capillary refill time of the tissue based on a time taken for at least one of the pulsation rate and the percutaneous arterial oxygen saturation, which change along with compression on the tissue, to return to a predetermined threshold range with respect to each value before the compression, and an output device that outputs information indicating the capillary refill time.

Rather than rely on variation from physician to physician and limited imaging information for assessing plaque vulnerability of a patient, medical imaging and other information are used by a machine-implemented classifier to predict plaque rupture. Anatomical, morphological, hemodynamic, and biochemical features are used in combination to classify plaque.

Systems and methods for monitoring patients with multiple chronic diseases are described. A system may include a health status monitor that receives diagnostic data including physiological signals sensed from a patient. The system may produce at least a first risk indication of the patient developing a first disease and a second risk indication of the patient developing a different second disease. The system may detect the first and second diseases from the physiological signals, and generate a composite health status indicator using the detections of the first and second diseases and the first and second risk indications. An alert of worsening health status may be generated if the composite detection score exceeds an alert threshold.

Systems and methods for monitoring patients with multiple chronic diseases are described. A system may include a health status monitor that receives diagnostic data including physiological signals sensed from a patient. The system may produce at least a first risk indication of the patient developing a first disease and a second risk indication of the patient developing a different second disease. The system may detect the first and second diseases from the physiological signals, and generate a composite health status indicator using the detections of the first and second diseases and the first and second risk indications. An alert of worsening health status may be generated if the composite detection score exceeds an alert threshold.

Systems are provided for generating data representing electromagnetic states of a heart for medical, scientific, research, and/or engineering purposes. The systems generate the data based on source configurations such as dimensions of, and scar or fibrosis or pro-arrhythmic substrate location within, a heart and a computational model of the electromagnetic output of the heart. The systems may dynamically generate the source configurations to provide representative source configurations that may be found in a population. For each source configuration of the electromagnetic source, the systems run a simulation of the functioning of the heart to generate modeled electromagnetic output (e.g., an electromagnetic mesh for each simulation step with a voltage at each point of the electromagnetic mesh) for that source configuration. The systems may generate a cardiogram for each source configuration from the modeled electromagnetic output of that source configuration for use in predicting the source location of an arrhythmia.

Systems and methods are disclosed for providing a cardiovascular score for a patient. A method includes receiving, using at least one computer system, patient-specific data regarding a geometry of multiple coronary arteries of the patient; and creating, using at least one computer system, a three-dimensional model representing at least portions of the multiple coronary arteries based on the patient-specific data. The method also includes evaluating, using at least one computer system, multiple characteristics of at least some of the coronary arteries represented by the model; and generating, using at least one computer system, the cardiovascular score based on the evaluation of the multiple characteristics. Another method includes generating the cardiovascular score based on evaluated multiple characteristics for portions of the coronary arteries having fractional flow reserve values of at least a predetermined threshold value.