Cognoa, Inc.

University of California

Perfect Daylight Limited

Brent Vaughan

Dennis Wall

Abdelhalim Abbas

Clara Lajonchere

Sharief Khalil Taraman

Jay Hack

Charlie Hack

Robert K Naviaux

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

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

The digital personalized medicine system uses digital data to assess or diagnose symptoms of a subject to provide personalized or more appropriate therapeutic interventions and improved diagnoses. The use of prioritized questions and answers with associated feature importance can be used to assess mental function and allow a subject to be diagnosed with fewer questions, such that diagnosis can be repeated more often and allow the dosage to be adjusted more frequently. Pharmacokinetics of the subject can be estimated based on demographic data and biomarkers or measured, in order to determine a treatment plan for the subject. Also, biomarkers can be used to determine when the patient may be at risk for experiencing undesirable side effects and the treatment plan adjusted accordingly.

Growing community of inventors

Portola Valley, CA, United States of America

Brent Vaughan