Currently submitted to: JMIR Formative Research
Date Submitted: May 4, 2026
Open Peer Review Period: May 4, 2026 - Jun 29, 2026
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Real-World Deployment of an Ethical AI-Assisted Tele-Ultrasound Platform for Endometriosis Diagnosis in the Brazilian Public Health System: The EndoConnect Alpha Case Study and Its Evolution into the NAM-Endora Framework
ABSTRACT
Background:
Endometriosis affects 10 % of reproductive-age women globally, with diagnostic delays of 7–10 years in Brazil’s SUS. Digital platforms offer promise, but few are ethically designed with AI for low-resource settings.
Objective:
To report real-world deployment of EndoConnect Alpha in SUS primary care, evaluate usability/acceptability, and describe its evolution into the NAM-Endora ethical AI framework.
Methods:
Applied methodological study. EndoConnect Alpha (React.js + Firebase) deployed in 10 SUS units (Ceará). n = 60 (45 patients, 15 professionals). Instruments: SUS, TAM, engagement metrics, clinical-psychosocial outcomes. Ethics CAAE 82094924.8.0000.5049. INPI BR5120250005556-0.
Results:
SUS 88.9 ± 9.8 (excellent); TAM 91.4.57/5. Trail completion 79 %. Pain reduction 23 % (VAS p=0.02), therapy adherence +17 %, anxiety −14 %. Strong SUS-TAM correlation (ρ=0.76, p<0.001).
Conclusions:
EndoConnect Alpha is feasible and impactful in SUS. NAM-Endora provides scalable ethical AI governance for LMICs. Multicenter validation planned. Clinical Trial: Not applicable (formative research)
Citation
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