2. Koçak B, et al. Bias in artificial intelligence for medical imaging: fundamentals, detection, avoidance, mitigation, challenges, ethics, and prospects. Diagn Interv Radiol. 2025;31(2):75-88. DOI: 10.4274/dir.2024.242854
3. Al Zaabi A, et al. Trends and Trajectories in the Rise of Large Language Models in Radiology: Scoping Review. JMIR Med Inform. 2025;13:e78041. DOI: 10.2196/78041
4. Muehlematter UJ, et al. Approval of artificial intelligence and machine learning-based medical devices in the USA and Europe (2015–20). Lancet Digital Health. 2021;3:e195-e203. DOI: 10.1016/S2589-7500(20)30292-2
O LAUDOS.Ai nasceu da evidência científica e da compreensão das necessidades reais do radiologista brasileiro. Ditado contextual, estruturação inteligente e comunicação de achados críticos — tudo em uma plataforma integrada, sob seu controle total.
Current workflow
Natural voice
Radiologists speak findings naturally while the platform handles structure, punctuation, and review.
Structured reports
Templates and fields preserve modality standards without blocking physician edits before signature.
Governance
Real adoption depends on access control, auditability, privacy, integrations, and operational traceability.