Ellipsis Health, Inc.

Amdocs Development Limited

Tomasz Rutowski

Michael Aratow

Mainul Islam

Amir Hossein Harati Nejad Torbati

David Lin

Robert Derward Rogers

Elizabeth E Shriberg

Yang Lu

Farshid Haque

Peter John Cogan

Paul Andrew Ferguson

Catherine Boothman

Piotr Chlebek

John Thomas Hereford

Melissa McCool

The present disclosure provides acoustic and natural language processing (NLP) models for predicting whether a subject has a behavioral or mental health state of interest based at least in part on input speech from said subject.

Acoustic and natural language processing models for speech-based screening and monitoring of behavioral health conditions

The present disclosure provides systems and methods for assessing a mental state of a subject in a single session or over multiple different sessions, using for example an automated module to present and/or formulate at least one query based in part on one or more target mental states to be assessed. The query may be configured to elicit at least one response from the subject. The query may be transmitted in an audio, visual, and/or textual format to the subject to elicit the response. Data comprising the response from the subject can be received. The data can be processed using one or more individual, joint, or fused models. One or more assessments of the mental state associated with the subject can be generated for the single session, for each of the multiple different sessions, or upon completion of one or more sessions of the multiple different sessions.

Systems and methods for mental health assessment

An event processing system, method, and computer program product are provided. A plurality of records are stored, including a plurality of events of different event types for a plurality of customers. In use, an indication is received in connection with one or more aspects associated with one or more of the events for one or more of the customers. Based on such indication, one or more subsets of the events of one or more of the records are identified. In some optional embodiments, such one or more event subsets are then processed to reduce noise therein, resulting in fewer events in the one or more event subsets. To this end, a result of the processing may be displayed in a variety of ways for a variety of purposes.

Event processing system, method, and computer program

A system, method, and computer program product are provided for identifying significant records (e.g. journeys, etc.). In use, a plurality of records including a plurality of events are stored. Further, an indication is received regarding at least one subset of the records. Thereafter, at least a portion of the events of the at least one subset of the records are processed to generate mean information such that the records of the at least one subset may be compared, utilizing the mean information. This may be accomplished while avoiding, at least in part, a covariance calculation, or in such a manner that the comparison is independent of such covariance calculation. A result of the comparison may be displayed.

System, method, and computer program for identifying significant records

A system, method, and computer program product are provided for identifying significant attributes of records (e.g. journeys, etc.). A plurality of records are stored, including a plurality of events with a plurality of attributes. Further, the attributes of the events are processed, utilizing machine learning. To this end, at least one of the attributes are identified as being significant, based on the processing. Such identified at least one attribute may then be displayed, etc.

System, method, and computer program for identifying significant attributes of records

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Gdansk, Poland

Tomasz Rutowski