Methods and apparatus for evaluating developmental conditions and providing control over coverage and reliability

Abstract

The methods and apparatus disclosed herein can evaluate a subject for a developmental condition or conditions and provide improved sensitivity and specificity for categorical determinations indicating the presence or absence of the developmental condition by isolating hard-to-screen cases as inconclusive. The methods and apparatus disclosed herein can be configured to be tunable to control the tradeoff between coverage and reliability and to adapt to different application settings and can further be specialized to handle different population groups.

Description

CROSS-REFERENCE[0001]The present application is a bypass continuation of International Patent Application No. PCT / US2017 / 061552, filed Nov. 14, 2017, which claims priority to U.S. Provisional Application No. 62 / 421,958, filed on Nov. 14, 2016, and U.S. Provisional Application No. 62 / 452,908, filed on Jan. 31, 2017, each of which application are herein incorporated in their entireties for all purposes.[0002]The subject matter of the present application is related to U.S. application Ser. No. 14 / 354,032, filed on Apr. 24, 2014, now U.S. Pat. No. 9,443,205, and U.S. application Ser. No. 15 / 234,814, filed on Aug. 11, 2016, the entire disclosures of which are incorporated herein by reference.BACKGROUND OF THE INVENTION[0003]Prior methods and apparatus for diagnosing and treating cognitive function attributes of people such as, for example, people with a developmental condition or disorder can be less than ideal in at least some respects. Unfortunately, a less than ideal amount of time, e...

AI Technical Summary

Benefits of technology

[0015]The methods and apparatus disclosed herein can account for different subject-specific dimensions such as, for example, a subject's age, a geographic location associated with a subject, a subject's gender or any other subject-specific or demographic data associated with a subject. In particular, the methods and apparatus disclosed herein can take different subject-specific dimensions into account in identifying the subject as at risk of having one or more cognitive function attributes such as developmental conditions, in order to increase the sensitivity and specificity of evaluation, diagnosis, or classification of the subject. For example, subjects belonging to different age groups may be evaluated using different machine learning ass

Problems solved by technology

Prior methods and apparatus for diagnosing and treating cognitive function attributes of people such as, for example, people with a developmental condition or disorder can be less than ideal in at least some respects.

Unfortunately, a less than ideal amount of time, energy and money can be required to obtain a diagnosis and treatment, and to determine whether a subject is at risk for decreased cognitive function such as, dementia, Alzheimer's or a developmental disorder.

The healthcare system is under increasing pressure to deliver care at lower costs, and prior methods and apparatus for clinically diagnosing or identifying a subject as at risk of a developmental disorder can result in greater expense and burden on the health care system than would be ideal.

Further, at least some subjects are not treated as soon as ideally would occur, such that the burden on the healthcare system is increased with the additional care required for these subjects.

The identification and treatment of cognitive function attributes, including for example, developmental disorders in subjects can present a daunting technical problem in terms of both accuracy and efficiency.

Many known methods for identifying such attributes or disorders are often time-consuming and resource-intensive, requiring a subject to answer a large number of questions or undergo extensive observation under the administration of qualified clinicians, who may be limited in number and availability depending on the subject's geographical location.

In addition, many known methods for identifying and treating behavioral, neurological, or mental health conditions or disorders have less than ideal accuracy and consistency, as subjects to be evaluated using such methods often present a vast range of variation that can be difficult to capture and classify.

Although prior lengthy tests with questions can be administered to caretakers such as parents in order to diagnose or identify a subject as at risk for a developmental condition or disorder, such tests can be quite long and burdensome.

For example at least some of these tests have over one hundred questions, and more than one such l

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