The present invention provides method for monitoring physiological status of an organ in a subject by monitoring morphological changes over time in transplanted tissue on an eye of the subject.

The present invention relates to a real-time parathyroid imaging apparatus including: a light source including an excitation filter capable of exciting parathyroid glands; and a camera including an image sensor and an emission filter of which a transmissivity ratio between a visible light region and a near-infrared emission wavelength region is N:1 (here, N<1). Through the present invention, a system may be implemented whereby a surgeon may acquire, in real-time during an operation, an autofluorescence image of the parathyroid glands by using a near-infrared light source, and an auto focus function may be used, and visible light and near-infrared autofluorescence images may be simultaneously fused and acquired without having to turn off the lights in an operating room.

One aspect of the invention relates to a method for intraoperative detection of parathyroid gland viability in a surgery, comprising obtaining speckle contrast images of a parathyroid gland of a patent; and displaying the speckle contrast images of the parathyroid gland in real-time.

A system includes a computing device that receives a query thyroid image, where the query thyroid image is an ultrasound image of a thyroid comprising a thyroid nodule of interest. The computing device processes the query thyroid nodule image using a machine learning model to identify at least one labelled thyroid image from a plurality of labelled thyroid images that is similar to the query thyroid nodule image. The plurality of labelled thyroid images are used as training data to generate the machine learning model. The at least one labelled thyroid image has labels associated therewith and comprises an ultrasound image of a thyroid nodule that has a confirmed diagnosis. The computing device generates an output report based on the labels associated with the at least one labelled thyroid image, where the output report indicates whether the thyroid nodule of interest resembles a malignant thyroid nodule or benign thyroid nodule.

A method for predicting thyroid dysfunction for a subject is disclosed. The method includes determining a target data based on a trigger signal; obtaining interval heart rates corresponding to the determined target date; obtaining, for the subject, a first pre-processing result for the obtained interval heart rates corresponding to the determined target date; obtaining, for the subject, at least one of concentration of hormone related to a thyroid corresponding to a reference date; obtaining, for the subject, a second pre-processing result for interval heart rates corresponding to the reference date; obtaining a difference of the first pre-processing result with respect to the second pre-processing result; and obtaining a prediction result for thyroid dysfunction obtained based on values including the at least one of concentration of hormone related to a thyroid corresponding to a reference date and the difference.

According to the present application, a computer-implemented method of predicting thyroid eye disease is disclosed. The method comprising: preparing a conjunctival hyperemia prediction model, a conjunctival edema prediction model, a lacrimal edema prediction model, an eyelid redness prediction model, and an eyelid edema prediction model, obtaining a facial image of an object, obtaining a first processed image and a second processed image from the facial image, wherein the first processed image is different from the second processed image, obtaining predicted values for each of a conjunctival hyperemia, a conjunctival edema and a lacrimal edema by applying the first processed image to the conjunctival hyperemia prediction model, the conjunctival edema prediction model, and the lacrimal edema prediction model, and obtaining predicted values for each of an eyelid redness and an eyelid edema by applying the second processed image to the eyelid redness prediction model and the eyelid edema prediction model.

The present invention relates to treatment of a psychiatric condition, for example resistant depression (RD), bipolar disorder (either threshold or sub-threshold) and/or major depressive disorder via application of repetitive transcranial magnetic stimulation with a drug treatment, in particular application of repetitive transcranial magnetic stimulation with treatment to modulate the activity of the neurones and induce neuroplasticity and the use of Thyroid hormone treatment to increase quantity or activity of thyroid hormones, for example for treatment of thyroid dysfunction. Patients may be selected for treatment by testing for the presence of normal thyroid function.

Provided is a method and apparatus for providing information needed for the diagnosis of lymph node metastasis of a thyroid cancer, and the method includes the steps of: acquiring medical images produced correspondingly to the continuous volumes of a body region including the neck; detecting at least one or more lymph nodes from the medical images through a first network function learned, the lymph nodes including at least one or more lymph nodes having higher lymph node metastasis risks than a given reference value; dividing the neck tissue around the thyroid into a plurality of compartments on the medical images through a second network function learned, based on the anatomical characteristics of the neck tissue; and matching diagnostic information including the information of the detected lymph nodes and the plurality of compartments with the medical images and displaying the diagnostic information on the medical images.

A system for dietary communications using intelligent systems regarding endocrinal measurements includes a computing device designed and configured to obtain a first endocrinal measurement relating to a user; compare the first endocrinal measurement to an endocrinal system effect; generate a body dysfunction label for the first endocrinal measurement as a function of the endocrinal system effect; identify a dietary communication as a function of the body dysfunction label, the first endocrinal measurement, and a first machine learning process, the first machine learning process trained using a first training set relating endocrinal measurements and body dysfunction labels to dietary communications; and present the dietary communication.

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).