AI Readiness in Healthcare

Healthcare AI Auditing & Risk Consulting

How do you know your healthcare AI is working well for everyone? 99.8% of funded AI interventions fail to meet basic quality standards. We ensure yours isn't one of them.

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Services

Comprehensive support for healthcare AI implementation

Healthcare Algorithm Audit

Comprehensive assessment of risks associated with clinical AI use cases.

Uses our AI Readiness Framework
Identifies fairness, equity, and validity issues
Delivers risk mitigation recommendations
Outputs: Algorithm Audit Report

Equity Testing & Validation

Analysis to measure bias and disparities in healthcare algorithms.

Validation across demographic subgroups
Tests for disparate impact
HIPAA-compliant analysis
Outputs: Equity Audit Report

AI Governance & Risk Management

Build infrastructure for responsible AI use.

Organization-level risk approach
Governance policy review
AI vendor procurement assistance
Outputs: Risk documentation

Clinical AI Monitoring

Real-time monitoring systems for deployed AI.

Identify key clinical and equity metrics
Calibrate thresholds and protocols
Integrate with analytics platforms

HTI-1 & Regulatory Compliance

Support for healthcare AI regulations.

Use-case-specific fairness metrics
External validation research
Compliance report preparation

Education & Training

Critical thinking about AI systems.

Workshops for clinical teams
Bespoke compliance training
Medical data annotation

Industries & Focus Areas

We partner with health systems, digital health companies, payers, and research institutions.

Clinical Decision Support

Risk Stratification

Diagnostic AI

Treatment Recommendations

HIV Prevention & Care

Population Health

Health Equity

Mental Health

AI Readiness Framework

When is a healthcare algorithm ready for deployment?

Data Availability

Is sufficient high-quality data available?

External Validity

Does precision create false confidence?

Explainability

Can clinicians trust the parameters?

Interpretability

Does transparency enable oversight?

Equity

Do averages mask disparities?

Readiness

Should implementation proceed?

In the News

Featured

Jan 2025

MIT Sloan AI in Healthcare Certification

Nyx Dynamics founder completes MIT Sloan Executive Education program on AI implementation in clinical settings.

Featured

Dec 2024

Healthcare AI Readiness Framework Published

Our six-question framework for evaluating clinical AI readiness now available for healthcare organizations.

Nov 2024

Nyx Dynamics Joins AI Safety Discussions

Contributing to national conversations on responsible healthcare AI deployment.

Oct 2024

HIV Prevention Algorithm Validation

Completed equity audit of PrEP eligibility algorithms, identifying disparities in underserved populations.

Principles

Context Matters

An algorithm isn't good or bad per se – it is just a tool. Who is using it, and for which patients? We go beyond accuracy metrics.

The Readiness Paradox

Rigorous validation exposes uncertainty rather than eliminating it. Computationally ready ≠ clinically proven.

Ethics Cannot Be Automated

There cannot be a universal checklist – clinical context is too important. Human judgment will always be essential.

Leadership

Adrian Charles Demidont, DO, FIDSA

Founder & CEO

Board-certified infectious diseases physician with 20+ years of clinical experience. Former Principal Medical Scientist at Gilead Sciences and Chief Medical Officer at Anchor Health Initiative. MIT Sloan AI in Healthcare certification. Peer-reviewed researcher in HIV prevention and implementation science.

MIT Sloan MITx Data Science FIDSA AAHIVS

Contact

Ready to ensure your healthcare AI works equitably for all patients?

Email: info@nyxdynamics.org

Phone: 203.247.1177

Address:
268 Post Road East, Suite 200
Fairfield, CT 06824

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