Cognoa, Inc.

Leland Stanford Junior University

Other

Dennis Wall

Brent Vaughan

Abdelhalim Abbas

Terry Allen Winograd

Nicholas Joseph Haber

Catalin Voss

Clara Lajonchere

Aaron Scott Kline

Jay Hack

Sharief Khalil Taraman

Charlie Hack

Jeffrey Ford Garberson

The methods and apparatus disclosed herein can diagnose or identify a subject as at risk of having one or more developmental disorders with fewer questions, decreased amounts of time, and determine a plurality of developmental disorders, and provide clinically acceptable sensitivity and specificity in a clinical environment. The methods and apparatus disclosed herein can be configured to diagnose or determine the subject as at risk of a developmental disorder among a plurality of developmental disorders, and decreasing the number of questions presented can be particularly helpful where a subject presents with a plurality of possible developmental disorders. A processor can be configured with instructions to identify a most predictive next question, such that a person can be diagnosed or identified as at risk with fewer questions.

Methods and apparatus to determine developmental progress with artificial intelligence and user input

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.

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

Disclosed herein is a machine learning platform and system for data analysis including for purposes of providing digital evaluations and therapeutics.

Machine learning platform and system for data analysis

Behavioral and mental health therapy systems in accordance with several embodiments of the invention include a wearable camera and/or a variety of sensors (accelerometer, microphone, among various other) connected to a computing system including a display, audio output, holographic output, and/or vibrotactile output to automatically recognize social cues from images captured by at least one camera and provide this information to the wearer via one or more outputs such as (but not limited to) displaying an image, displaying a holographic overlay, generating an audible signal, and/or generating a vibration.

Systems and methods for using mobile and wearable video capture and feedback plat-forms for therapy of mental disorders

Disclosed herein are platforms, systems, devices, methods and media for model optimization and data analysis using machine learning. Input data can be processed and analyzed to identify relevant discriminating features, which can be modeled using a plurality of machine learning models. A computing device can be configured with one or more optimized models for categorizing input data.

Model optimization and data analysis using machine learning techniques

Growing community of inventors

Palo Alto, CA, United States of America

Dennis Wall