A system, method, and computer readable media are provided for obtaining a first set of skin data from an image capture system including at least one ultraviolet (UV) image of a user's skin. Performing a correction on the skin data using a second set of skin data associated with the user. Quantifying a plurality of skin parameters of the user's skin based on the first skin data, including quantifying a bacterial load. Quantifying the bacterial load by applying a brightness filter to isolate portions of the at least one UV image containing fluorescence, applying a dust filter, identifying portions of the at least one UV image that contain fluorescence due to bacteria, and determining a quantity of bacterial load in the users skin. Determining, using a machine learning model, an output associated with a normal skin state of the user and a current skin state of the user.

Systems and methods that facilitate determining interaction between medications and the brain using a brain measure and a brain model. Hidden nervous system states are difficult to predict, diagnose, and treat with therapeutic medications. A Dual Neural Machine Translation (d-NMT) algorithmic system that utilizes sets of parameters for a relapsing-remitting MS model based on patient medical records and adjusts a method of parameterization to produce a model that can match patients' medical records and medical images. These parameters are can be used by a therapeutic determining model to recommend therapies, doses, and time courses accurately.

A biological information displaying apparatus according to an embodiment includes a picture obtaining apparatus and a processor. The picture obtaining apparatus obtains a picture signal of a predetermined site of a subject as a moving image. The processor generates a hue moving image by extracting a luminance or an image-based photoplethysmogram (iPPG) related to a pulse wave for each pixel of the moving image and assigning a hue in accordance with a value of luminance information or iPPG information. The processor displays the generated hue moving image such that the hue moving image is superimposed on an image of the subject.

At least one example embodiment relates to a computer-implemented method for providing stroke information, the method comprising receiving computed tomography imaging data of an examination area of a patient, the examination area of the patient comprising a plurality of brain regions, at least one brain region of the plurality of brain regions being affected by a stroke, receiving brain atlas data, generating registered imaging data based on the computed tomography imaging data and the brain atlas data, the registered imaging data being registered to the brain atlas data, generating the stroke information regarding the stroke based on a set of algorithms and the registered imaging data, and providing the stroke information.

An information processing device includes: an acquirer that acquires observation results obtained from a time-lapse image of a target object; and a controller that indicates, in a display image, analysis results visually representing the observation results and an increase/decrease time indicating an amount of time required to increase or decrease a predetermined value related to the target object. When a setting for a section in the analysis results has been received, the controller indicates, in the display image, the increase/decrease time corresponding to the section that has been set.

There is provided a computer implemented method for detection of likelihood of malignancy in an anatomical image of a patient for planning treatment thereof, comprising: receiving a pair of images that are either of a same patient or from two different patients, wherein the pair of images comprises anatomically corresponding anatomical images each depicting internal anatomical structures of the patient, feeding the pair of images into a model, outputting by the model, an indication of whether the pair of images are of a same patient or not, and generating an indication of likelihood of malignancy when the model wrongly outputs that the pair of images are not of the same patient, when in fact the pair of images are of the same patient, wherein treatment of the patient is planned according to the indication of likelihood of malignancy.

In medical examination of breast cancer, a lesion computer-aided detection is performed in real time and with high accuracy, and a burden on a medical worker is reduced. A medical image processing apparatus that processes a medical image includes: a detection unit configured to detect a lesion candidate region; a validity evaluation unit configured to evaluate validity of the lesion candidate region by using a normal tissue region corresponding to the detected lesion candidate region; and a display unit configured to determine display content to a user by using an evaluation result.

An information processing apparatus includes at least one processor, and the processor derives a property for at least one predetermined property item which is related to a structure of interest included in an image. The processor specifies a basis region serving as a basis for deriving the property related to the structure of interest for each property item and derives a basis image including the basis region.

The present disclosure provides a non-contact heart rhythm category monitoring system, which includes steps as follows. Facial images are continuously captured through an image sensor; images of a continuous target area for a predetermined duration are extracted from the facial images; non-contact physiological signal related to heartbeats are captured from the images of the continuous target area; the non-contact physiological signal are classified into a normal heart rhythm, an atrial fibrillation and a non-atrial fibrillation arrhythmia.

Provided is a data processing method according to the present disclosure including: a scan data acquiring operation of acquiring scan data expressing an object, a reliability determining operation of determining a reliability of at least one evaluation area including at least one unit area for evaluating the scan data, and an indicating operation of indicating the evaluation area as a predetermined mark depending on the reliability of the evaluation area.