Built for the Complexity of ADHD Assessment
Multimodal by Design. AI-Assisted. Clinician-Governed.
NVOX brings clinical history, collateral evidence, assessment performance, and information-quality context into one structured Clinical Decision Support workflow.
AI-assisted methods help organize evidence, surface relevant patterns, and support clinical review. They do not make autonomous diagnostic decisions or replace licensed professional judgment.
Clinical assessment infrastructure, not a single AI model.
Development and Clinical Foundation
Built Over Years, Not Around a Single Model
Development of the NVOX assessment framework began in 2021, following an initial research phase focused on the limitations and inefficiencies of traditional ADHD assessment.
From the beginning, NVOX was designed as clinical assessment infrastructure, not as a single model attempting to determine whether someone has ADHD. The framework brings together multisource evidence collection, structured assessment tasks, information-quality review, AI-assisted evidence organization, report workflow, clinical review, and governance.
Its development has been informed by expertise across psychiatry, neuropsychology, psychology, neurology, education, and neuroscience.
AI is part of the system. It is not the system.
Core Assessment Technology Modules
Specialized Modules. One Integrated Assessment Workflow.
NVOX combines structured clinical profiling, objective task performance, evidence organization, and information-quality review within its clinical assessment workflow.
Each clinical assessment component contributes organized information for clinician review. No component independently determines the diagnosis.
NVOX Cognitive and Behavioral Profile™
Structures developmental, behavioral, functional, educational, medical, and contextual information for clinical review.
NVOX dCPT™
Provides task derived data related to attention regulation, response timing, consistency, inhibition, distractor sensitivity, and performance stability.
Quality and Interpretability Layer
Evaluates whether video, audio, device, environmental, cooperation, and signal conditions support responsible use of the available information.
AI-Assisted Evidence Organization
Organizes multimodal information, surfaces relevant patterns and inconsistencies, and prepares clinician readable evidence for professional review.
Explore Assessment Layers
Research Modules
NCBA and WAVE are separate investigational research modules. Their outputs are not used in diagnostic determinations.
AI-Assisted Evidence Organization
Turning Multimodal Information Into Clear, Reviewable Clinical Evidence
NVOX uses AI-assisted methods to organize structured and narrative clinical information, collateral input, task performance, and quality context into clear evidence layers that clinicians can review.
The process preserves the identity of each information source and helps show where the evidence converges, where sources differ, what may be missing, and which areas require further professional review.
Source Separation and Traceability
Preserves separation and traceability across clinical history, collateral input, task results, and quality context.
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Identification of Convergence and Gaps
Shows where evidence layers support one another, diverge, or require additional interpretation.
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Completeness and Quality Review
Helps identify information that is missing, limited, conflicting, or affected by technical or contextual constraints.
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Case Preparation for Clinical Review
Presents complex information in a clear, traceable, and source grounded structure for professional review, interpretation, and feedback.
AI helps organize and present the evidence.
The clinician determines its clinical meaning.
Model Development and Lifecycle Controls
Built for Multimodal Model Development, Not One Time Automation
NVOX is designed to support ongoing model development around multimodal assessment data, signal quality, evidence organization, and clinician reviewed workflows.
Model related work is designed to support pattern detection, evidence organization, signal interpretation support, quality review, workflow consistency, report usability, future validation planning, and continued improvement of the assessment infrastructure.
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Version Control
Data Quality Review
Quality Monitoring
Human Review
Release Controls
Protected Implementation Boundaries
NVOX is building model infrastructure
to make complex clinical evidence
more usable, reviewable, and scalable.
The model lifecycle is governed through these controls to support responsible development over time.
Model related work is not designed to replace clinician judgment or produce autonomous diagnostic decisions.
Implementation level details, including model architecture, feature maps, training logic, calibration methods, thresholds, protected scoring logic, and security sensitive infrastructure details, are not disclosed publicly.
Current Expansion Beyond ADHD
A Modular Architecture Already Expanding to Additional Clinical Applications
NVOX is currently developing and rolling out additional clinical and neurodevelopmental applications built on the same modular evidence architecture.
Each application follows its own condition specific clinical design, evidence development, quality controls, clinician review, governance, and validation pathway.
The architecture is already expanding. Each application is developed and governed according to its own clinical and evidence requirements.
Signal Aware Technology
Quality Before Interpretation
NVOX does not treat every captured signal as a clinical finding.
Where NVOX Labs research analytics are generated, their interpretability depends on camera quality, lighting, audio quality, device type, language, accent, fatigue, reading ability, emotional state, medication, and the assessment environment.
Signal quality and interpretability are therefore part of the workflow.
A limited signal is not treated as a normal result.
Missing information is not automatically treated as negative evidence.
A layer that cannot be interpreted responsibly is identified, qualified, or bounded.
NCBA and WAVE are investigational NVOX Labs research modules.
Their outputs are not used in NVOX diagnostic determinations.
Less noise. More clinical signal.
Technology Ecosystem and Compute Readiness
Infrastructure Designed for Multimodal Development and Signal Processing
NVOX technology infrastructure supports model development, testing, signal processing, quality review, workflow improvement, and responsible lifecycle management.
The infrastructure is designed to support GPU accelerated and other high performance computing capabilities where appropriate.
These capabilities support the technical development of the platform while clinical interpretation remains clinician-governed.
Member of NVIDIA Inception
Technology and Clinical Boundaries
AI-Assisted, Not AI Authorized
NVOX uses AI-assisted and signal aware technology to organize evidence, surface relevant patterns, support quality review, and improve workflow consistency and report usability.
The technology does not independently make diagnostic decisions, authorize clinical reports, determine eligibility for services or accommodations, or replace licensed clinical review.
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Technology Supports
Evidence organization
Pattern and inconsistency identification
Signal quality and interpretability context
Workflow consistency
Report usability
Licensed Clinicians Remain Responsible For
Clinical interpretation
Report authorization according to the applicable pathway
Client feedback
Final recommendations
Appropriate next steps
NVOX organizes the evidence.
The reviewing clinician determines its clinical meaning.
Explore Validation Readiness