A method for assessing idea generation and generating recommendations regarding idea implementation includes providing to each of a plurality of assessment subjects, at a first time, a first assessment prompt. The method includes receiving a first response to the first assessment prompt from each of the plurality. The method includes providing, to each of the plurality of assessment subjects, at a second time subsequent to the first time, a second assessment prompt and receiving from each of the plurality of assessment subjects, a second response. The method includes receiving, from each of the plurality of assessment subjects, a self-evaluation of the first response and the second response. The method includes identifying, based on the analysis, at least one idea generation characteristic for each of the plurality of assessment subjects. The method includes dynamically updating a representation of a graph displaying a comparison of the idea generation characteristic across assessment subjects.

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).

A method of providing personalized guideline information for a user in a predetermined domain, in which a set of personality types is defined for users of said predetermined domain, includes: determining, by a personality type recognizer, a personality type for a user in order to assign the personality type to said user, selecting a personality-typed machine learning model from a model pool of personality-typed machine learning models based on the personality type of said user, where the selected personality-typed machine learning model is used to initialize an individual personalized machine learning model of said user, and generating, by the individual personalized machine learning model of said user, a recommendation prediction, the recommendation prediction is presented as a guideline information to said user.

Systems, methods, and computer-executable instructions for identifying a candidate include receiving unscripted communication, the unscripted communication comprising communication from a first speaker. Properties of the unscripted communication are extracted. A psychographic classifier classifies the first speaker into a psychographic category based on the extracted properties. An aggregate psychographic category of a team is determined based on psychographic categories of each of the team members of the team. A weakness in the aggregate psychographic category of the team is determined. A new team member that has a psychographic category that addresses the weakness in the aggregate psychographic category of the team is identified. A recommendation that the first speaker become a team member of the team is provided.

Provided is a cognitive function testing system capable of efficiently and objectively measuring cognitive functions related to, for example, ADHD and easily collecting detailed data. In addition, a cognitive function estimation system is provided to enable estimating and determining the probability of an individual having a disorder such as ADHD after the cognitive functions related to, for example, ADHD have been efficiently and objectively measured. In contrast to the conventional Stroop interference test that uses paper, one problem is displayed on one screen, and not only the correctness result of the problem for the test subject, but also coordinate information for when the test subject responds by manipulating a touch panel display, are recorded in a problem answer table. Furthermore, an estimation calculation based on a learning algorithm can be used to estimate the degree of cognitive function of the test subject.

Embodiments of the present systems and methods may provide a non-invasive system to measure and integrate behavioral and cognitive features enabling early detection and progression tracking of degenerative disease. For example, a method of detecting neurodegenerative disease may comprise measuring functioning of at least one of the motor system, cognitive function, and brain activity of a subject during everyday life and analyzing the gathered at least one motor system data, cognitive function data, and brain activity data of the subject.

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.

Methods for the diagnosis, prognosis, patient stratification and prediction of pharmacological response in patients afflicted by psychiatric disorders based on electroretinography (ERG) parameters are described.

Subject matter disclosed herein may relate to systems, devices, and/or processes for processing signals and/or states representative of behavioral and/or biological state.

A method and system for creating virtual personality renderings generated from a personality profile exclusively associated with an individual, the rendering depicted in the form of a geometric object in virtual 3D space representing personality traits of the individual. The rendering may comprise a virtual shape having a surface area divided into multiple regions, with each region representative of a personality trait. Personality datapoints may be introduced into the base personality model to generate a unique rendering which is unique for the individual's personality. As personality datapoints are added to personality profile, multiple vectors may project from the base model, causing the base personality model to reconfigure into a non-uniform shape, which is representative of the individual's unique personality. The vectors may represent the magnitude of personality traits.