Developing the Future of
Lab AI Strategy.
I am building a proprietary framework that combines strategic planning with working code. My goal is to provide labs with honest assessments and functional prototypes proving technical feasibility before they invest in production.
Why I Am Building This Framework
To Prevent Costly Failures
70% of AI projects in healthcare fail. I am developing a pre-assessment protocol designed specifically to catch failure points before labs spend budget on vendors.
To Prove It Works First
Labs shouldn't have to trust sales decks. My methodology focuses on building "Proof of Concept" prototypes using anonymized data to validate technical feasibility early.
To Secure Executive Buy-In
I am researching the most effective ways to present AI ROI to CFOs. My framework aims to replace vague promises with data-backed financial projections.
To Ensure Vendor Neutrality
The industry needs objective advice. My research is independent of any software vendor, focusing solely on what architecture is best for the lab's specific workflow.
The Problem With Current Options
My research addresses the gap between high-level consulting and expensive software sales.
❌ Traditional Consultants
- • 40-slide PowerPoint presentations
- • Generic vendor lists
- • High-level "roadmaps" only
- • No technical capability
"Looks good on paper, but will it work?"
❌ AI Solution Vendors
- • Pre-built platform demos
- • Sales-driven promises
- • Long-term contract lock-in
- • Hard to customize
"Are they just selling their platform?"
✅ The Solution I Am Building
- • Strategic assessment + Code
- • Working prototypes (Anonymized data)
- • Technical validation of use-cases
- • 100% Vendor Neutral
"Validating feasibility before investment."
Lab Report Analyzer
AI-Powered Diagnostic Interpretation
Transform complex lab reports into clear, actionable insights with AI-driven analysis that flags critical values, identifies patterns, and recommends next steps.
Key Capabilities
Automatic detection of out-of-range values with severity flagging
Clinical interpretation of complex biomarker patterns
Personalized recommendations based on patient history
Multi-report trend analysis over time
Demo for educational purposes only • Not for clinical decision-making
AI Use Cases for Diagnostic Labs
Explore common AI applications and how they solve specific challenges in diagnostic laboratory operations.
Predictive Quality Control
Predict QC failures 6-8 hours before they occur, preventing costly instrument downtime and sample re-runs.
Turnaround Time Forecasting
Predict TAT 12-24 hours in advance to optimize staffing, manage expectations, and prevent bottlenecks.
Lab Data Anomaly Detection
Automatically detect unusual patterns in lab results, instrument performance, or operations that may indicate problems.
Prototypes In Development
I am currently building and testing these models using public datasets to prove technical feasibility.
📊 Predictive TAT Forecasting
Predicting turnaround times 6-24 hours in advance based on order volume, test mix, and staffing patterns.
⚠️ QC Failure Prediction
Detecting instrument drift or QC shifts 4-8 hours before failure using anomaly detection on QC result patterns.
🔬 Digital Pathology Analysis
Automating cell counting and identifying regions of interest using computer vision on histopathology images.
Seeking Input From Lab Leaders
Lab Directors
I am interviewing directors to understand the specific hurdles in building business cases for AI investment.
Operations Leaders
I am gathering data on where operational bottlenecks occur most frequently to refine my forecasting models.
Compliance Teams
I am developing templates for AI governance and seeking feedback on CLIA-specific compliance requirements.
Engagement Frameworks
I am currently refining these engagement models through active pilots. My goal is to standardize these frameworks to ensure labs get consistent, high-value outcomes.
*Pricing structures will be finalized upon commercial launch in early 2026.*
Strategic Assessment
A diagnostic framework designed to assess AI readiness, identify high-ROI opportunities, and build a vendor-neutral implementation roadmap.
Key Components:
- ✓Readiness Gap Analysis
- ✓Vendor-Neutral Roadmap
- ✓Data Governance Audit
- ✓Executive ROI Modeling
Current Status: Methodology Phase
View DetailsPrototyping Pilot
My core research focus. A collaborative pilot where we build a functioning AI model using your anonymized data to prove technical feasibility before production.
Key Components:
- ✓Feasibility Validation
- ✓Custom Python Models
- ✓Performance Metrics Report
- ✓Code-First Proof of Concept
- ✓Stakeholder Demo
Current Status: Accepting Beta Partners
View DetailsSpecialized Modules
Targeted research modules for specific lab challenges, including staff training protocols, vendor evaluation matrices, and compliance document templates.
Key Components:
- ✓Staff Literacy Workshops
- ✓Vendor Selection Matrix
- ✓Business Case Development
- ✓Regulatory Checklists
Current Status: In Development
View DetailsWhy I Prioritize Prototyping
The Industry Standard:
- • Theoretical slide decks
- • "Trust us" vendor promises
- • Expensive licenses upfront
- • Risk: High
My R&D Approach:
- • Working code & data models
- • Validated on your specific use case
- • Feasibility proven before purchase
- • Risk: Low
The Goal: I am building a methodology that forces AI projects to prove their value technically before a lab is asked to sign a massive vendor contract.
Latest Insights & Articles
Actionable advice and deep dives into the topics that matter most to modern diagnostic labs.
Ready-to-Implement Code Solutions
Explore my library of pre-tested AI code, validated demos, and deployment frameworks built to bypass prototyping and rapidly integrate intelligence into your healthcare lab.
AI Lab Report Analyzer
Transform unstructured lab reports into actionable insights instantly. AI-powered analysis that extracts, interprets, and flags critical values from any lab report format.
AI Readiness & Strategy Assessment
A comprehensive audit of your data, systems, and goals, culminating in a custom AI implementation roadmap.
Follow the Research
I publish updates on my prototype development and strategic frameworks. Read the latest insights on how AI is actually working in the lab environment.
View Insights & UpdatesProject Status: Research & Development
MichelleVision is currently in a Soft Launch / Beta Phase.
I am currently focused on building the technical frameworks and prototypes that will form the basis of my future advisory services. All prototypes shown are built using public, anonymized datasets. I am actively seeking conversation partners to help shape this research, but I am not yet accepting commercial contracts.
Connect & Follow Progress
I am currently in the Research & Development phase, refining AI frameworks for diagnostic labs.
If you are a lab leader interested in beta-testing these strategies, or simply want to discuss your current data challenges to help shape this research, please send me a note below.