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Canvas Dx is intended for use by healthcare providers as an aid in the diagnosis of Autism Spectrum Disorder (ASD) for patients ages 18 months through 72 months who are at risk for developmental delay based on concerns of a parent, caregiver, or healthcare provider. The device is not intended for use as a stand-alone diagnostic device but as an adjunct to the diagnostic process.

Canvas Dx is a prescription diagnostic aid for healthcare professionals (HCP) considering the diagnosis of Autism Spectrum Disorder (ASD) in patients 18 months through 72 months of age at risk for developmental delay. The subject device is identical to the Cognoa ASD Diagnosis Aid which was authorized under DEN200069 and was renamed Canvas Dx shortly thereafter. Canvas Dx consists of Software as a Medical Device (SaMD) together with several medical device data system (MDDS) components. The SaMD components consist of the following: - **Device inputs:** - Device Input 1: The answers to the Caregiver Questionnaire - Device Input 2: Patient Video Analysis - Device Input 3: The answers to the Healthcare Provider Questionnaire - A machine learning (ML) algorithm ('Algorithm') modeled after standard medical evaluation methodologies and drives the device outputs. - **Device outputs:** - 'Positive for autism' - 'Negative for autism' - 'Indeterminate' The MDDS components that are compatible with the SaMD components include the following: - A caregiver facing mobile application, which provides Device Input 1; - A video analyst system, which provides Device Input 2; - A healthcare provider portal, which provides Device Input 3; - Several supporting software and backend services and infrastructure, including privacy and security encryption and infrastructure in compliance with HIPAA and other best practices. The subject of this submission is the inclusion of a Predetermined Change Control Plan (PCCP) that allows updates to the Canvas Dx model and performance thresholds.

The EarliPoint System device is indicated as a tool to aid qualified clinicians in the diagnosis and assessment of Autism Spectrum Disorder (ASD) in children ages 16 months through 30 months, who are at risk based on concerns identified by a parent, caregiver, or healthcare provider.

The EarliPoint system uses an eye tracker to capture the patient's looking behavior while viewing a series of videos. The system then remotely analyzes the looking behavior data using software and outputs a diagnosis of the patient's ASD status and associated developmental delay indicies. The EarliPoint System device consists of the following: • Eye-tracking module and a separate Operator Module that can control the Eye-tracking module remotely. The patient sits on a chair and the Eye-tracking module is adjusted by the operator such that the patient's eyes are within the specification of the eye tracking window. • Eye-tracking module captures the patient visual response to social information provided in the form of a series of age-appropriate videos. • Operator's module is used to initiate and monitors the session remotely • WebPortal securely stores all patient information, analyzes the eye tracking data, and outputs the results. Users can retrieve the results directly from the web-portal. • Artificial intelligence software analyzes the eye-tracking data and provides a diagnosis for ASD. In addition, it also outputs 3 developmental delay indices (called EarliPoint Severity Indices) that proxy the ADOS-2 and Mullen validated ASD instruments Social Disability Index correlates and proxies ADOS-2 Verbal Ability Index correlates and proxies the age equivalent Mullen Verbal Ability score Non-verbal Ability Index correlates and proxies the age equivalent non-verbal Mullen Ability score

The EarliPoint System is indicated for use in specialized developmental disabilities centers as a tool to aid clinicians in the diagnosis and assessment of ASD patients ages 16 months through 30 months.

The device is a more compact version of the predicate device but otherwise has similar functions and features. The system uses an eye tracker to capture the patient's looking behavior while viewing a series of videos. The system then remotely analyzes the looking behavior data using software and outputs a diagnosis of the patient's ASD status and assesses the symptoms associated with ASD. The system has two modules: EarliPoint System consists of the following: - Eye-tracking module and a separate Operator Module that can control the Eye-tracking module remotely. The patient sits on a chair and the Eye-tracking module is adjusted by the operator such that the patient's eyes are within the specification of the eye tracking window - -Eye-tracking module captures the patient visual response to social information provided in the form of a series of age-appropriate videos - Operator's module is used to initiate and monitors the session remotely - - -WebPortal securely stores all patient information, analyzes the eye tracking data, and outputs the results. Users can retrieve the results directly from the web-portal. - -Artificial intelligence software analyzes the eye-tracking data and provides a diagnosis for ASD. In addition, it also outputs 3 indices (called EarliPoint Severity Indices) that proxy the ADOS-2 and Mullen validated ASD instruments - o Social Disability Index correlates and proxies ADOS-2 - O Verbal Ability Index correlates and proxies the age equivalent Mullen Verbal Ability score - O Non-verbal Ability Index correlates and proxies the age equivalent non-verbal Mullen Ability score The eye-tracker used in the EarliPoint device has similar capability as the eye tracker used in the predicate device.

The EarliPoint System is indicated for use in specialized developmental disabilities centers as a tool to aid clinicians in the diagnosis and assessment of Autism Spectrum Disorder (ASD) for patients ages 16 months through 30 months.

The EarliPoint System is a medical device for diagnosis of Autism Spectrum Disorder (ASD) in children. EarliPoint System consists of the following: - EarliPoint WebPortal to enter the patient information and for access to the patient evaluation results, - EarliPoint Device with eye-tracking capability captures the patient visual response to social information provided in the form of a series of age-appropriate videos - Artificial intelligence software analyzes the eye-tracking data and provides a diagnosis for ASD. - Eye-tracking data also outputs 3 indices (called EarliPoint Severity Indices) that proxy the ADOS-2 and Mullen validated ASD instruments - Social Disability Index correlates and proxies ADOS-2 - Verbal Ability Index correlates and proxies the age equivalent Mullen Verbal Ability score - Non-verbal Ability Index correlates and proxies the age equivalent non-verbal Mullen Ability score

The Cognoa ASD Diagnosis Aid is intended for use by healthcare providers as an aid in the diagnosis of Autism Spectrum Disorder (ASD) for patients ages 18 months through 72 months who are at risk for developmental delay based on concerns of a parent, caregiver, or healthcare provider. The device is not intended for use as a stand-alone diagnostic device but as an adjunct to the diagnostic process.

The Cognoa ASD Diagnosis Aid is a software as a medical device (SaMD) that utilizes a machine-learning algorithm that receives independent information from caregivers or parents, trained analysts, and healthcare professionals (HCPs) to aid in the diagnosis of ASD. It consists of multiple software applications and hardware platforms. Input data is acquired via a Mobile App, a Video Analyst Portal, and a HCP Portal. - . Mobile App: User interface (UI) for the caregiver or parent to upload videos of the patient via Wi-Fi connection and answer questions about key developmental behaviors. Interfaces with Application Programming Interface (API) server for transmission and management of patient data. Compatible with both iOS (versions 12 and 13) and Android platforms (versions 9 and 10). - Video Analyst Portal: UI for trained analysts to review uploaded patient videos . remotely and answer questions about the patients' behaviors observed in the videos. - . HCP Portal: UI for the HCP to answer questions about key developmental behaviors for the patient's age group, view device output and access the interactive dashboard to view all patient results, patient videos, answers to questionnaires administered and device performance data. Compatible with computer operating systems macOS (Catalina or Mojave) and Windows 10, and browsers Safari (versions 12 or 13) and Chrome (versions 84 or 85). Following analysis of the input data, the Cognoa ASD Diagnosis Aid machine-learning algorithm produces a single scalar value between (1) and (6) which is then compared to preset thresholds to determine the classification. If the value is greater than the upper threshold, then the device output is 'Positive for ASD.' If the value is less than the lower threshold, then the device output is 'Negative for ASD.' If the available information does not allow the algorithm to render a reliable result, the device output is 'No Result.'