Machine learning in an artificial pancreas is described. An artificial pancreas system may include a wearable glucose monitoring device, an insulin delivery system, and a computing device. Broadly speaking, the wearable glucose monitoring device provides glucose measurements of a person continuously. The artificial pancreas algorithm, which may be implemented at the computing device, determines doses of insulin to deliver to the person based on a variety of aspects for the purpose of maintaining the person's glucose within a target range, as indicated by those glucose measurements. The insulin delivery system then delivers those determined doses to the person. As the artificial pancreas algorithm determines insulin doses for the person over time and effectiveness of the insulin doses to maintain the person's glucose level in the target range is observed, an underlying model of the artificial pancreas algorithm may be updated to better determine insulin doses.

Machine learning in an artificial pancreas is described. An artificial pancreas system may include a wearable glucose monitoring device, an insulin delivery system, and a computing device. Broadly speaking, the wearable glucose monitoring device provides glucose measurements of a person continuously. The artificial pancreas algorithm, which may be implemented at the computing device, determines doses of insulin to deliver to the person based on a variety of aspects for the purpose of maintaining the person's glucose within a target range, as indicated by those glucose measurements. The insulin delivery system then delivers those determined doses to the person. As the artificial pancreas algorithm determines insulin doses for the person over time and effectiveness of the insulin doses to maintain the person's glucose level in the target range is observed, an underlying model of the artificial pancreas algorithm may be updated to better determine insulin doses.

Machine learning in an artificial pancreas is described. An artificial pancreas system may include a wearable glucose monitoring device, an insulin delivery system, and a computing device. Broadly speaking, the wearable glucose monitoring device provides glucose measurements of a person continuously. The artificial pancreas algorithm, which may be implemented at the computing device, determines doses of insulin to deliver to the person based on a variety of aspects for the purpose of maintaining the person's glucose within a target range, as indicated by those glucose measurements. The insulin delivery system then delivers those determined doses to the person. As the artificial pancreas algorithm determines insulin doses for the person over time and effectiveness of the insulin doses to maintain the person's glucose level in the target range is observed, an underlying model of the artificial pancreas algorithm may be updated to better determine insulin doses.

Machine learning in an artificial pancreas is described. An artificial pancreas system may include a wearable glucose monitoring device, an insulin delivery system, and a computing device. Broadly speaking, the wearable glucose monitoring device provides glucose measurements of a person continuously. The artificial pancreas algorithm, which may be implemented at the computing device, determines doses of insulin to deliver to the person based on a variety of aspects for the purpose of maintaining the person's glucose within a target range, as indicated by those glucose measurements. The insulin delivery system then delivers those determined doses to the person. As the artificial pancreas algorithm determines insulin doses for the person over time and effectiveness of the insulin doses to maintain the person's glucose level in the target range is observed, an underlying model of the artificial pancreas algorithm may be updated to better determine insulin doses.

Machine learning in an artificial pancreas is described. An artificial pancreas system may include a wearable glucose monitoring device, an insulin delivery system, and a computing device. Broadly speaking, the wearable glucose monitoring device provides glucose measurements of a person continuously. The artificial pancreas algorithm, which may be implemented at the computing device, determines doses of insulin to deliver to the person based on a variety of aspects for the purpose of maintaining the person's glucose within a target range, as indicated by those glucose measurements. The insulin delivery system then delivers those determined doses to the person. As the artificial pancreas algorithm determines insulin doses for the person over time and effectiveness of the insulin doses to maintain the person's glucose level in the target range is observed, an underlying model of the artificial pancreas algorithm may be updated to better determine insulin doses.

Disclosed are examples that include receiving information related to ingestion of a meal. The information may include a coarse indication of a size of the meal, a relative time of ingestion of the meal, and a general composition indication of the meal. A blood glucose measurement value received within a predetermined time range of a relative time of ingestion of the meal may be identified. Settings for a delay and an extend parameter and a delivery constraint may be determined. A meal model may be modified using the determined settings for the delay parameter, the extend parameter, and the delivery constraint. The modified meal model may be used to determine a dose of insulin to be delivered in response to the received information. An instruction indicates a determined dose of insulin to be delivered may be output for delivery to a drug delivery device.

A surgical tool includes opposing jaws, handles and at least one pressure sensor. Another aspect of a surgical tool includes opposing jaws with each having an organ-contacting surface area of at least 50 mm.sup.2. A further aspect of a surgical tool includes an electronic controller connected to at least one pressure sensor and automatically adapted to calculate or determine an organ-hardness from a sensor when jaws are moved to an organ-compressing position. In yet another aspect of a surgical tool, a pressure sensor is mounted to a pancreas-compressing surface and a displacement transducer or sensor is mounted to and/or located within a handle coupled to the surface, and an electronic controller is mounted to and/or located within the handle for calculating a hardness of a pancreas and/or other organ.

A system and medical device for the electromagnetic tracking of a medical instrument transported through the medical device. The medical device has a central axis and a channel that receives and transports a medical instrument through the medical device. The channel extends to a distal portion of the medical device and connects with an opening in the medical device that is not aligned with the central axis. The medical device includes a tracking component that is a plurality of coordinated electromagnetic sensors for generating a virtual axis of travel for the medical instrument, with the virtual axis passing through the opening of the device and being aligned with tool insertion axis.

Systems and methods are provided for neuro stimulation. In one implementation, a system is provided that includes a stimulator introduced into tissue at a target location and a central controller that communicates wirelessly with the stimulator. The stimulator includes a power system that receives wireless energy transmission, and an electrode system that transmits an electrical pulse for stimulating the target location. The central controller includes a power system that wirelessly delivers power to the stimulator, a communication system that wirelessly communicates with the stimulator, and a processing system that controls the power system and the communication system. The central controller may instruct the stimulator to transmit one or more electrical pulses to the target location to affect an endocrine function (e.g., affect the glucose level of a patient).

In a method for generating a surrogate marker based on medical image data mapping an image region, the medical image data is detected using a first interface, a first subregion of the image region is selected by segmenting a first structure included in the image region, a first property of the first subregion is extracted, the surrogate marker is determined based on the first property, and the surrogate marker is provided using a second interface.