xRead - Incorporating Artificial Intelligence into Clinical Practice (March 2026)

Ng et al. BMC Medical Informatics and Decision Making

(2025) 25:236

Page 7 of 24

Ven

dor ini

tiated

Sam

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Size

Netherlands Outpatient 430 No

USA Outpatient 11 No

Pre-post quality im provement study Mix of medical specialties USA Outpatient 46 Yes Prospective qual ity improvement study Ambulatory settings USA Outpatient 45 Yes

Moryousef et al., 2025 [35] Multiple AI scribes (including Nabla, Scribe MD) NLP Evaluation study Urology Canada Outpatient 20 No Shah et al., 2025 [36] DAX Copilot ASR, LLM, NLP Prospective qual ity improvement study Ambulatory settings USA Outpatient 48 Yes Abbreviations: AEGIS: Automated Evaluation of Gastrointestinal Symptoms; ASR: Automatic Speech Recognition; CRF: Conditional random field; DAX: Dragon Ambient eXperience; LLM, large language model; RNN: Recurrent Neural Network

Study Software/Model Type of AI Model Study Design Clinical Setting Country Inpatient/ Outpatient van Buchem et al., 2024 [31]

consultation, focused on various presentations of chest pain

Dialogue scripts based off

real encounters from various specialties (e.g. otolaryn

gology, internal medicine,

family medicine, pediatrics and urgent care)

Biro et al., 2025 [32] Ambient Digital Scribe (ADS) LLM Instrument validation

NLP, LLM System evaluation Simulated internal medicine

Duggan et al., 2025 [33] DAX Copilot ASR, LLM, NLP

Ma et al., 2025 [34] DAX Copilot ASR, LLM, NLP

Autoscriber (transformer-based speech-to-text model, fine tuned on proprietary clinical data for transcription and a

mixture of large language models such as GPT-3.5 and GPT-4, combined with a tailored prompt structure and additional rules for summarization)

Table 1 (continued)