Abstract: The present invention relates to a pharmaceutical composition for preventing or treating non-alcoholic fatty liver disease, comprising trametinib. The composition of the present invention, which comprises trametinib, reduces steatosis, inflammation, or ballooning in liver tissue where non-alcoholic fatty liver has been induced; reduces the level of fibrosis of inflammation induced by non-alcoholic fatty liver; and reduces the weight of a liver that has increased due to non-alcoholic fatty liver disease. Accordingly, the composition of the present invention can be provided for use in preventing or treating metabolic liver disease, including non-alcoholic fatty liver disease.

Abstract: Disclosed are a method and an apparatus for managing a user profile. A user profile management method performed by a server according to an example embodiment includes creating a plurality of profiles corresponding to a user account, receiving a view request for a profile of the other user account in a predetermined relationship with the user account from a user terminal logged in with the user account, providing a UI of a profile of the other user account including an interfacing object regarding the profile of the user account to the user account, receiving an input for selecting a profile to be displayed on the other user terminal logged in the other user account, among a plurality of profiles corresponding to the user account through the interfacing object, and matching the other user account with the selected profile.

Abstract: Provided is an artificial intelligence (AI) system for simulating human brain functions such as perception and judgment by using a machine learning algorithm such as deep learning, and an application thereof. Provided is a device and method for recommending products to a user on the basis of facial expression information of the user through the AI system. The method, performed by the device, of recommending products includes: displaying a product selected by the user; obtaining user's facial expression information with respect to the displayed product; determining the user's satisfaction with the displayed product based on the obtained user's facial expression information; selecting a product set to be recommended to the user from among a plurality of product sets based on the determined user's satisfaction; and displaying at least one product included in the selected product set.

Abstract: An image processing apparatus and an image processing method for estimating a region of interest based on information of interest learned by a data recognition model satisfying a certain condition from among a plurality of data recognition models and for setting a focus are provided. The image processing apparatus includes estimating a region of interest by using a rule-based algorithm or an artificial intelligence (AI) algorithm. When estimating a region of interest by using an AI algorithm, the image processing apparatus may estimate a region of interest by using a machine learning algorithm, a neural network algorithm, or a deep learning algorithm.

Abstract: An image processing apparatus and an image processing method for estimating a region of interest based on information of interest learned by a data recognition model satisfying a certain condition from among a plurality of data recognition models and for setting a focus are provided. The image processing apparatus includes estimating a region of interest by using a rule-based algorithm or an artificial intelligence (AI) algorithm. When estimating a region of interest by using an AI algorithm, the image processing apparatus may estimate a region of interest by using a machine learning algorithm, a neural network algorithm, or a deep learning algorithm.

Abstract: An electronic apparatus is provided. The electronic apparatus includes at least one processor configured to detect, by a sensor, a driving state of a vehicle or a driving state of another vehicle in a vicinity of the vehicle while the vehicle is being driven, obtain state data including the driving state of the vehicle and the driving state of the other vehicle, and use at least one data recognition model to determine a dangerous situation of the vehicle after a certain period of time while the vehicle is being driven, based on the obtained state data. The electronic apparatus may predict a dangerous situation of the vehicle by using a rule-based algorithm or an artificial intelligence (AI) algorithm. The electronic apparatus predicts the dangerous situation of the vehicle by using at least one of machine learning, a neural network, and a deep learning algorithm.

Abstract: An electronic apparatus is provided. The electronic apparatus includes at least one processor configured to detect, by a sensor, a driving state of a vehicle or a driving state of another vehicle in a vicinity of the vehicle while the vehicle is being driven, obtain state data including the driving state of the vehicle and the driving state of the other vehicle, and use at least one data recognition model to determine a dangerous situation of the vehicle after a certain period of time while the vehicle is being driven, based on the obtained state data. The electronic apparatus may predict a dangerous situation of the vehicle by using a rule-based algorithm or an artificial intelligence (AI) algorithm. The electronic apparatus predicts the dangerous situation of the vehicle by using at least one of machine learning, a neural network, and a deep learning algorithm.

Abstract: Provided is an artificial intelligence (AI) system for simulating human brain functions such as perception and judgment by using a machine learning algorithm such as deep learning, and an application thereof. Provided is a device and method for recommending products to a user on the basis of facial expression information of the user through the AI system. The method, performed by the device, of recommending products includes: displaying a product selected by the user; obtaining user's facial expression information with respect to the displayed product; determining the user's satisfaction with the displayed product based on the obtained user's facial expression information; selecting a product set to be recommended to the user from among a plurality of product sets based on the determined user's satisfaction; and displaying at least one product included in the selected product set.

Abstract: The present disclosure relates to an artificial intelligence (AI) system utilizing a machine learning algorithm such as deep learning, and application of the same. In particular, a method for controlling an electronic device of the present disclosure comprises the steps of: obtaining image data and supplementary data including data on a user from an external terminal connected to the electronic device; generating feature data for determining the user's actual emotion by using the image data and the supplementary data; and determining the user's actual emotion by inputting the feature data into an emotion recognition model.

Abstract: An image processing apparatus and an image processing method for estimating a region of interest based on information of interest learned by a data recognition model satisfying a certain condition from among a plurality of data recognition models and for setting a focus are provided. The image processing apparatus includes estimating a region of interest by using a rule-based algorithm or an artificial intelligence (AI) algorithm.

Abstract: An electronic apparatus is provided. The electronic apparatus includes at least one processor configured to detect, by a sensor, a driving state of a vehicle or a driving state of another vehicle in a vicinity of the vehicle while the vehicle is being driven, obtain state data including the driving state of the vehicle and the driving state of the other vehicle, and use at least one data recognition model to determine a dangerous situation of the vehicle after a certain period of time while the vehicle is being driven, based on the obtained state data. The electronic apparatus may predict a dangerous situation of the vehicle by using a rule-based algorithm or an artificial intelligence (AI) algorithm. The electronic apparatus predicts the dangerous situation of the vehicle by using at least one of machine learning, a neural network, and a deep learning algorithm.