Idea
Local AI system delivering accurate preoperative patient answers from vetted FAQs to improve clinical communication and privacy.
Research Paper
Core Innovation
This paper introduces LENOHA, a safety-first AI system that avoids free-text generation by returning clinician-curated FAQ answers verbatim, ensuring high accuracy and privacy. It uses a high-precision sentence-transformer classifier to route queries locally, achieving near-perfect accuracy with minimal energy consumption and latency. This approach structurally eliminates generation-induced errors common in clinical AI communication.
Market Size (TAM)
$20–50B TAM for healthcare AI communication tools; $2–10B SAM from hospitals and clinics focused on preoperative patient engagement. Driven by increasing demand for personalized patient communication and privacy compliance.
Potential Customers & Pain Points
- Hospitals Needing Efficient Preoperative Patient Communication
- Clinics Facing Time-Pressured Workflows
- Healthcare Providers Concerned With Patient Privacy
- Medical Facilities In Bandwidth-Limited Environments
- Developers Of Clinical AI Tools Seeking Energy-Efficient Solutions
Business Model
Subscription-based licensing for healthcare institutions with options for on-premises deployment and support services.
Competitive Landscape
- GPT-4o
- Gemini AI
- IBM Watson Health
Implementation Challenges
- Integration With Existing Clinical Workflows
- Regulatory Approval For Medical AI Use
- Clinician Trust And Adoption
Validation Strategy
- Conduct multi-domain clinical trials with diverse patient populations
- Obtain regulatory certifications for medical device software
- Partner with hospitals for pilot deployments and feedback
Research Paper Overview
A Locally Executable AI System for Improving Preoperative Patient Communication: A Multi-Domain Clinical Evaluation
Summary
This paper presents LENOHA, a local-first AI system that uses a high-precision sentence-transformer classifier to route clinical queries and return verbatim answers from a clinician-curated FAQ, avoiding free-text generation. Evaluated on tooth extraction and gastroscopy domains with expert-reviewed datasets, LENOHA achieved near-perfect accuracy comparable to GPT-4o and Gemini, while consuming significantly less energy and maintaining low latency. The system supports privacy, sustainability, and equitable deployment in bandwidth-limited environments by structurally avoiding generation-induced errors in clinical communication.