Abstract: A Computer-Aided Diagnosis (CAD) apparatus and a CAD method are provided. The CAD apparatus includes an automatic diagnoser configured to perform automatic diagnosis using an image that is received from a probe, and generate diagnosis information including results of the automatic diagnosis. The CAD apparatus further includes an information determiner configured to determine diagnosis information to be displayed among the generated diagnosis information, based on a manual diagnosis of a user, and a display configured to display the received image and the determined diagnosis information.

Abstract: A nickname management apparatus includes a speech agent configured to recognize a speech of a user to obtain nickname information of a device, and a nickname manager configured to determine a device corresponding to the nickname information from one or more devices on a network, and register the named device based on the determination.

Abstract: A Computer-Aided Diagnosis (CAD) apparatus and a CAD method are provided. The CAD apparatus includes an automatic diagnoser configured to perform automatic diagnosis using an image that is received from a probe, and generate diagnosis information including results of the automatic diagnosis. The CAD apparatus further includes an information determiner configured to determine diagnosis information to be displayed among the generated diagnosis information, based on a manual diagnosis of a user, and a display configured to display the received image and the determined diagnosis information.

Abstract: Technology related to an apparatus and method for supporting a diagnosis of a lesion is provided. The apparatus includes a standard image determiner to determine, as a standard image, an image where a region of interest (ROI) is detected among a plurality of images received from an image collecting device, a candidate image extractor to extract one or more candidate images with respect to the determined standard image, a comparison image selector to select one or more comparison images for supporting a diagnosis of the ROI from the one or more candidate images, and an interface to provide a user with an output result of the standard image and the one or more selected comparison images.

Abstract: A Computer-Aided Diagnosis (CAD) apparatus and a CAD method are provided. The CAD apparatus includes an automatic diagnoser configured to perform automatic diagnosis using an image that is received from a probe, and generate diagnosis information including results of the automatic diagnosis. The CAD apparatus further includes an information determiner configured to determine diagnosis information to be displayed among the generated diagnosis information, based on a manual diagnosis of a user, and a display configured to display the received image and the determined diagnosis information.

Abstract: An apparatus and method for adaptive computer-aided diagnosis (CAD) are provided. The adaptive CAD apparatus includes an image analysis algorithm selector configured to select an image analysis algorithm based on a speed of a probe or a resolution of a current image frame obtained by the probe; and an image analyzer configured to detect and classify a region of interest (ROI) in the current image frame using the selected image analysis algorithm.

Abstract: A computer-aided diagnosis (CAD) apparatus and method. The CAD apparatus includes an area divider configured to divide a current image frame into a first area and a second area based on location of a region of interest (ROI) detected in a previous image frame. The CAD apparatus further includes a functional processor configured to perform different functions of the CAD apparatus for the first area and the second area.

Abstract: A system to generate a diagnosis model includes: a preprocessor configured to preprocess time-series data observed from a patient having a disease; a time-series analyzer configured to produce a data feature by applying an analysis model for a time-series variability analysis to the preprocessed time-series data; and a model generator configured to extract the produced data feature and to generate the diagnosis model based on the extracted produced data feature.

Abstract: An intelligent dialog processing apparatus and method. The intelligent dialog processing apparatus includes a speech understanding processor, of one or more processors, configured to perform an understanding of an uttered primary speech of a user using an idiolect of the user based on a personalized database (DB) for the user, and an additional-query processor, of the one or more processors, configured to extract, from the primary speech, a select unit of expression that is not understood by the speech understanding processor, and to provide a clarifying query for the user that is associated with the extracted unit of expression to clarify the extracted unit of expression.

Abstract: A nickname management apparatus includes a speech agent configured to recognize a speech of a user to obtain nickname information of a device, and a nickname manager configured to determine a device corresponding to the nickname information from one or more devices on a network, and register the named device based on the determination.

Abstract: A screen navigation apparatus includes a command receiver configured to receive an input voice command regarding navigation of a screen, and a processor configured to interpret the voice command based on an analysis result of content displayed on a screen and compose a command executable by the screen navigation apparatus and perform navigation of the screen.

Abstract: A Computer-Aided Diagnosis (CAD) apparatus and a CAD method are provided. The CAD apparatus includes an automatic diagnoser configured to perform automatic diagnosis using an image that is received from a probe, and generate diagnosis information including results of the automatic diagnosis. The CAD apparatus further includes an information determiner configured to determine diagnosis information to be displayed among the generated diagnosis information, based on a manual diagnosis of a user, and a display configured to display the received image and the determined diagnosis information.

Abstract: An apparatus and a method predict a patient's potential change of Coronary Artery Calcification (CAC) level using various risk factors including a Coronary Artery Calcification Score (CACS). The apparatus includes a receiving unit, a cluster determining unit, a risk factor score extracting unit, a prediction model storage unit, a prediction model learning unit, and a predicting unit, and the method includes a receiving process, a risk factor score extracting process, and an operation performing process.

Abstract: An apparatus and method for adaptive computer-aided diagnosis (CAD) are provided. The adaptive CAD apparatus includes an image analysis algorithm selector configured to select an image analysis algorithm based on a speed of a probe or a resolution of a current image frame obtained by the probe; and an image analyzer configured to detect and classify a region of interest (ROI) in the current image frame using the selected image analysis algorithm.

Abstract: A computer-aided diagnosis (CAD) apparatus and method. The CAD apparatus includes an area divider configured to divide a current image frame into a first area and a second area based on location of a region of interest (ROI) detected in a previous image frame. The CAD apparatus further includes a functional processor configured to perform different functions of the CAD apparatus for the first area and the second area.

Abstract: Technology related to an apparatus and method for supporting a diagnosis of a lesion is provided. The apparatus includes a standard image determiner to determine, as a standard image, an image where a region of interest (ROI) is detected among a plurality of images received from an image collecting device, a candidate image extractor to extract one or more candidate images with respect to the determined standard image, a comparison image selector to select one or more comparison images for supporting a diagnosis of the ROI from the one or more candidate images, and an interface to provide a user with an output result of the standard image and the one or more selected comparison images.

Abstract: An apparatus that supports a rehabilitation of a brain-damaged patient, including a patient condition analyzer configured to generate a patient condition scenario about a brain condition of a patient based on brain-related information of the patient, a network model determiner configured to determine a network model to be applied to the patient using the patient condition scenario, and a rehabilitation model generator configured to generate a rehabilitation model to be applied to the patient based on the determined network model.

Abstract: An apparatus and a method predict a patient's potential change of Coronary Artery Calcification (CAC) level using various risk factors including a Coronary Artery Calcification Score (CACS). The apparatus includes a receiving unit, a cluster determining unit, a risk factor score extracting unit, a prediction model storage unit, a prediction model learning unit, and a predicting unit, and the method includes a receiving process, a risk factor score extracting process, and an operation performing process.

Abstract: A method of predicting a potential degree of Coronary Artery Calcification (CAC) risk includes receiving a patient's medical test data relating to CAC; determining a cluster to which the patient's medical test data belong based on an age of the patient; extracting a risk factor score including at least two Coronary Artery Calcification Scores (CACSs) from the medical test data; storing a plurality of prediction models used for predicting a potential degree of CAC risk; and predicting a potential degree of CAC risk at a specific point in time by applying a CACS growth rate of the patient's medical test data calculated using the at least two CACSs of the patient's medical test data and the extracted risk factor score to a prediction model corresponding to the determined cluster to which the patient's medical test data belong among the plurality of prediction models.

Abstract: An apparatus and a method predict an upcoming stage of carotid stenosis. The apparatus includes a receiving unit, a cluster determining unit, a risk factor score extracting unit, a prediction model storage unit, and a predicting unit. The method includes receiving a patient's medical test data relating to carotid stenosis; determining a cluster to which the patient's medical test data belong based on a gender of the patient; extracting from the patient's medical test data a risk factor score comprising a result of carotid stenosis ultrasonography; storing a plurality of prediction models used to predict an upcoming stage of carotid stenosis; and obtaining an outcome by applying a value indicating a stage of carotid stenosis corresponding to the result of carotid stenosis ultrasonography and the extracted risk factor score to the prediction model corresponding to the determined cluster among the plurality of prediction models.