A data set of visuals of faces and extracted face property data are generated and linked to face characteristics data provided by a representative set of humans that rate the visuals of these faces with respect to their face characteristics. Further face property data of these visuals of faces is extracted and together with the generated data set used to train an artificial intelligence. The artificial intelligence is used to analyse a visual of the person's face and generate a data set of modifications based on a selected desired characteristic(s) and modifications achievable by at least one cosmetic and/or medical treatment. The visual of the face of the person is modified based on the data set of modifications and the computer-modified visual of the desired face of the person with the modification of the face achievable by the least one proposed cosmetic and/or medical treatment is generated and displayed.

A dementia symptom detection system includes an information processor which determines the level of dementia of a user based on (i) a reference value which is for an index corresponding to behavioral and psychological symptoms of dementia and which is determined based on the history of the activity amount stored in storage and the history of device operation information stored in the storage, and (ii) a personal value of the user which is for the index and which is determined based on the detected activity amount of the user and the obtained device operation information of the user.

A technique for enabling efficient retrieval of a digital representation of personality data of a user (402) by a client device (406) from a server (404) is disclosed, wherein the digital representation of the personality data is processed at the client device (406) to provide a user-adapted service to the user (402). A method implementation of the technique is performed by the server (404) and comprises storing a neural network being trained to compute personality data of a user based on input obtained from the user (402), receiving, from the client device (406), a request for a digital representation of personality data for a user (402), and sending, to the client device (406), the requested digital representation of the personality data of the user (402), wherein the personality data of the user is computed using the neural network based on input obtained from the user (402).

In an illustrative embodiment, systems and methods for automating candidate video assessments include receiving a submission from a candidate for an available position including baseline response video segments and question response video segments. The system can determine, from detected nonverbal features within the baseline response video segments, nonverbal baseline scores. For each of the interview questions, candidate response attributes can be detected including a response direction, a response speed, and nonverbal features. A nonverbal reaction score is calculated from the detected nonverbal features and the baseline scores. A response score can be calculated from the response direction and response speed, and a trustworthiness score is determined based on a correspondence between the response score and the nonverbal reaction score. A next interview question can be determined in real-time from a benchmarked version of the response score. Overall scores reflecting candidate trustworthiness can be presented within a user interface screen.

A computer-based system and associated processes are disclosed for making personality-related recommendations to an entity. The system receives indications of one or more personality attributes of an entity. The system acquires indications of one or more personality attributes of a desired partner of the entity. The system applies a mathematical model to the one or more personality attributes of the entity and the one or more personality attributes of the desired partner of the entity. The mathematical model calculates one or more recommended changes to the personality attributes of the entity to increase a predicted relationship satisfaction score between the entity and the desired partner. The system selects a recommended action from a database of recommended actions, based at least in part on the recommended changes to the personality attributes of the entity. The system presents the recommended action.

An exemplary system, method, and computer-accessible medium for determining a position or a characteristic of a target(s) for a transcranial magnetic stimulation (TMS) treatment of a patient(s) can be provided, which can include, for example, receiving imaging information of a portion(s) of a head of the patient(s), and determining the position or the characteristic of the target(s) for the TMS treatment of the patient(s) based on the imaging information. The imaging information can be magnetic resonance imaging information. The imaging information can include information regarding a brain and a skull of the patient(s). The position or the characteristic of the target(s) can be determined by identifying (i) the skull, and (ii) a parcel in a section(s) of a brain of the patient(s). The parcel can a dorsolateral prefrontal cortex (DLPFC) parcel. The DLPFC parcel can be identified using a parcellation procedure, which can be a human connectome pipeline procedure.

A method and system that includes at least one processor, the at least one computer in communication with at least one data storage unit, the at least one computer programmed and/or configured to: generate a plurality of dance sequences; associate or cause the association of each of the plurality of dance sequences with at least one dance corpus classification; generate, for each of the plurality of users, a user profile; receive, from each of the plurality of users, at least one preference data; associate or causing the association of each of the user's profile with at least one preference data; and generate a recommendation of a dance sequence for each of the plurality of users.

A device control apparatus (110) includes a personality-information acquiring unit (114) that acquires personality information indicating a personality of a user, a control-method specifying unit (115) that specifies a device control method that is a control method for a device (101) used by the user from the personality information and a lifestyle pattern of the user, and a control unit (116) that controls the device (101) in accordance with the device control method.

A computerized method for performing psychoanalysis on a human being, the method performed on a computing device having a display screen operating a graphical user interface, the method including the steps of providing an image to the computing device, the image representing human, animal, human-like, or animal-like facial features, generating a mirrored image from the provided image about a vertical mirror axis with a data processor of the computing device, partially superposing the provided image and the mirrored image to create a vertical axi-symmetric image, one side of the vertical mirror axis showing a portion of the provided image, the other side showing a portion of the mirrored image, and displaying the vertical axi-symmetric image on the graphical user interface of the computing device.

A technique for providing a user-adapted service to a user is disclosed. A method implementation of the technique is performed by a computing system and comprises obtaining (S1002) a digital representation of personality data of a user, the personality data of the user being computed based on input regarding the user, wherein the input regarding the user includes actual personality information of the user, the actual personality information specifically relating to the user-adapted service and including at least one of: a current mood of the user at the time of providing the user-adapted service to the user, one or more preferences of the user specifically relating to the user-adapted service, and one or more goals of the user specifically relating to the user-adapted service; and processing (S1004) the digital representation of the personality data to provide a user-adapted service to the user.