Systems and methods for providing a universal platform for at-home health testing and diagnostics are provided herein. In particular, a health testing and diagnostic platform is provided to connect medical providers with patients and to generate a unique, private testing environment. In some embodiments, the testing environment may facilitate administration of a medical test to a patient with the guidance of a proctor. In some embodiments, the patient may be provided with step-by-step instructions for test administration by the proctor within a testing environment. The platform may display unique, dynamic testing interfaces to the patient and proctor to ensure proper testing protocols and accurate test result verification.

This application relates to a method of constructing a training program for improving symptoms of a mild cognitive impairment patient. In one aspect, the method includes arranging, on designated days, direct training algorithms regarding at least one of visualization, fusion, or semantic word fluency directly related to a cognitive function area and controlling the arranged direct training algorithms to be output to a user terminal according to the designated days, and receiving a result value from the user terminal. The method may also include calculating an achievement level for each direct training algorithm, based on the result value, and determining one of the direct training algorithms based on the calculated achievement level. The method may further include rearranging the direct training algorithms, together with the determined direct training algorithm based on both the calculated achievement level and a training algorithm matched to the determined direct training algorithm.

Non-limiting examples of the present disclosure relate to application of artificial intelligence (AI) processing to generate classifications of user activity for a group of users. For example, a classification prediction is generated indicating whether students in an educational class are predicted, over a predetermined time period, to have a high or low activity level based on contextual analysis of multiple types of user-driven events. As user activity data is typically quite robust, the present disclosure applies dimensionality reduction processing to efficiently manage user activity data and further improve accuracy in generating downstream binary classifications. A dimensionality reduction transformation of user activity data results in a low-dimensional representation of input feature data that is contextually relevant for generating a binary classification. Derived classifications are then utilized to generate data insights pertaining to user activity levels of one or more users. Data insights are can then be rendered for presentation.

Children are spending an enormous amount of time on computer screens without receiving any educational benefit for doing so. The present invention advantageously Automatically Converts children's entertainment screen time into learning screen time. This is referred to as Auto-Conversion of Entertainment Screen Time into Learning Time. A novel Continuous Engagement Method During Learning keeps the learner engaged in academic functioning (where engagement would otherwise be continuously declining). The present invention solves a critical problem for special learners (e.g., those with ADHD, autism, dyslexia, or memory impairment) who have a high affinity for screen time and cannot access traditional reading instruction. An Artificial Intelligence (AI) architecture is used to customize the type of instruction the learner receives based upon academic progress and to customize delivery of the instruction itself by closely monitoring the learner's emotional mood state and sustained attention.

Systems and methods of automatically distilling concepts from math problems and dynamically constructing and testing the creation of math problems from a collection of math concepts comprising: providing a user interface to a user; receiving as input: a math problem; one or more math concepts; and/or a user data packet; extracting and compiling a concept cloud of one or more CLIs that comprise the mathematical concepts embodied in the input, describe the operation of the one or more math concepts, or relate to the UDP, respectively; generating one or more math problem building blocks from the concept cloud CLIs; applying a mathematical rules engine to the one or more math problem building blocks to build one or more additional math problems; and returning to the user, through the user interface, the one or more additional math problems built from the CLIs that define the concept cloud extracted from the input.

Systems and methods of automatically distilling concepts from math problems and dynamically constructing and testing the creation of math problems from a collection of math concepts comprising: providing a user interface to a user; receiving as input: a math problem; one or more math concepts; and/or a user data packet; extracting and compiling a concept cloud of one or more CLIs that comprise the mathematical concepts embodied in the input, describe the operation of the one or more math concepts, or relate to the UDP, respectively; generating one or more math problem building blocks from the concept cloud CLIs; applying a mathematical rules engine to the one or more math problem building blocks to build one or more additional math problems; and returning to the user, through the user interface, the one or more additional math problems built from the CLIs that define the concept cloud extracted from the input.

Systems and methods are provided for preparing, taking and scoring a test, and reporting the results of the test. The methods include electronically storing questions for a test in a database, and inputting teacher preferences for taking the test. The method also comprises electronically transmitting contact data associated with the test to students, so the students can access the test. The method also comprises authenticating student identification when the test is accessed and applying the teacher preferences. The method further comprises electronically selecting test questions for the student based on the teacher preferences applicable to the student. Still further, the method involves electronically submitting answers to the test questions. In addition, the method comprises electronically scoring the answers to the test questions based on the teacher preferences, including electronically sending student test results to the teacher, including a summary of questions requiring manual review for each student.

Systems and methods are provided for preparing, taking and scoring a test, and reporting the results of the test. The methods include electronically storing questions for a test in a database, and inputting teacher preferences for taking the test. The method also comprises electronically transmitting contact data associated with the test to students, so the students can access the test. The method also comprises authenticating student identification when the test is accessed and applying the teacher preferences. The method further comprises electronically selecting test questions for the student based on the teacher preferences applicable to the student. Still further, the method involves electronically submitting answers to the test questions. In addition, the method comprises electronically scoring the answers to the test questions based on the teacher preferences, including electronically sending student test results to the teacher, including a summary of questions requiring manual review for each student.

Example implementations disclosed herein can be used to generate student user-specific customized hybrid educational documents. Such implementations include systems, methods, and devices for determining an attention span profile associated with a particular student user, and generating a custom educational document in response to the attention span profile. Student user experience feedback and test results determined from the use of the customized educational document can be assessed to update the student user's attention span profile. The updated student user attention span can then be used to update the customized educational document.

Example implementations disclosed herein can be used to generate student user-specific customized hybrid educational documents. Such implementations include systems, methods, and devices for determining an attention span profile associated with a particular student user, and generating a custom educational document in response to the attention span profile. Student user experience feedback and test results determined from the use of the customized educational document can be assessed to update the student user's attention span profile. The updated student user attention span can then be used to update the customized educational document.