A system and method for predicting mild cognitive impairment (MCI) related diagnosis and prognosis utilizing hybrid machine learning. More specifically, the system and method produce predictions of MCI conversions to dementia and prognosis related thereof. Using available medical imaging and non-imaging data a diagnosis and prognosis model is trained using transfer learning. A platform may then receive a request from a clinician for a target patient's diagnosis or prognosis. The target patient's medical data is retrieved and used to create a model for the target patient. Then details of the target patient's model and the diagnosis and prognosis model are compared, a prediction is generated, and the prediction is returned to the clinician. As new medical data becomes available it is fed into the respective model to improve accuracy and update predictions.

Controlling the illumination at an endpoint to a communication session by transmitting, over the communication session, the color of the light to be emitted by the display of the receiving endpoint. In a particular embodiment, a method includes, during a video communication session between a first endpoint operated by a first user and a second endpoint operated by a second user, transmitting first video, comprising a solid color image, from the first endpoint to the second endpoint over the video communication session, wherein the first video is prominently displayed at the second endpoint. At the first endpoint, the method provides receiving second video from the second endpoint. The second video is captured at the second endpoint while the first video is being displayed at the second endpoint. The method also includes displaying the second video to the first user.

An example method includes obtaining, a virtual model of a portion of an anatomy of a patient obtained from a virtual surgical plan for an orthopedic joint repair surgical procedure to attach a prosthetic to the anatomy; identifying, based on data obtained by one or more sensors, positions of one or more physical markers positioned relative to the anatomy of the patient; and registering, based on the identified positions, the virtual model of the portion of the anatomy with a corresponding observed portion of the anatomy.

An example method includes obtaining, a virtual model of a portion of an anatomy of a patient obtained from a virtual surgical plan for an orthopedic joint repair surgical procedure to attach a prosthetic to the anatomy; identifying, based on data obtained by one or more sensors, positions of one or more physical markers positioned relative to the anatomy of the patient; and registering, based on the identified positions, the virtual model of the portion of the anatomy with a corresponding observed portion of the anatomy.

This invention provides a method to optimize an x-ray beam for more than one structure within the field of view. The preferred embodiment comprises a modular construction of a collimator comprising multiple materials of varying thickness. A first attenuation is performed by the first portion of the collimator to optimize a first anatomic feature and a second attenuation is performed by the second portion of the collimator to optimize a second anatomic feature.

In this patent, an improved multi-user extended reality viewing technique is disclosed. A first user and a second user can be geographically separated and view the same volume. The first user can manipulate a virtual object and the second user can see the manipulated virtual object. A set of techniques are disclosed herein to cause the virtual object as it is presented to each user to be eye appealing and prevent dizziness and nausea.

Computer and mobile device-based systems and computer-implemented methods are described for automated medication adherence improvement for patients in medication-assisted treatments. The computer and mobile device-based systems includes modules and components to help patients in identifying prescribed medications, logging medication events, and to provide patients with personalized and targeted adherence enhancing interventions consisting of short questions, tips, advices, suggestions, strategies etc. by applying data mining and statistical analysis techniques on the individual and population-level data collected primarily from the same system.

Disclosed is a care device recommendation server providing a service for recommending a skin care device for a user, the care device recommendation server including: a data management unit configured to obtain face images of the user from a shin measurement device including a camera and a display; a skin condition determination unit configured to determine a first skin condition of the user corresponding to a first time point at which the face images are obtained, based on the obtained the face images; a care device recommendation unit configured to determine the skin care device for the user among a plurality of care devices included in a care device DB based on the determined first skin condition; a care device control value-providing unit configured to provide a first control value of the skin care device corresponding to the first skin condition to each of a user terminal of the user and the skin measurement device; a care device control unit configured to remotely control the care device such that the skin care device is driven by the control value; and a history provision unit configured to provide information about a previous skin condition of the user, which corresponds to each of the face images of the user obtained from the data management unit, to the user terminal.

Disclosed is a care device recommendation server providing a service for recommending a skin care device for a user, the care device recommendation server including: a data management unit configured to obtain face images of the user from a shin measurement device including a camera and a display; a skin condition determination unit configured to determine a first skin condition of the user corresponding to a first time point at which the face images are obtained, based on the obtained the face images; a care device recommendation unit configured to determine the skin care device for the user among a plurality of care devices included in a care device DB based on the determined first skin condition; a care device control value-providing unit configured to provide a first control value of the skin care device corresponding to the first skin condition to each of a user terminal of the user and the skin measurement device; a care device control unit configured to remotely control the care device such that the skin care device is driven by the control value; and a history provision unit configured to provide information about a previous skin condition of the user, which corresponds to each of the face images of the user obtained from the data management unit, to the user terminal.

In a multi-session imaging study, information from a previous imaging session is stored in a Binary Large Object (BLOB). Current emission imaging data are reconstructed into a non-attenuation corrected (NAC) current emission image. A spatial transform is generated aligning a previous NAC emission image from the BLOB to the current NAC emission image. A previous computed tomography (CT) image from the BLOB is warped using the spatial transform, and the current emission imaging data are reconstructed with attenuation correction using the warped CT image. Alternatively, low dose current emission imaging data and a current CT image are acquired, a spatial transform is generated aligning the previous CT image to the current CT image, a previous attenuation corrected (AC) emission image from the BLOB is warped using the spatial transform, and the current emission imaging data are reconstructed using the current CT image with the warped AC emission image as prior.