Article

Assessing the Effectiveness of Automatic Speech Recognition Technology in Emergency Medicine Settings: A Comparative Study of Four AI-powered Engines

2024-08-17

Abstract excerpt

<title>Abstract</title> <p>Purpose Cutting-edge automatic speech recognition (ASR) technology holds significant promise in transcribing and recognizing medical information during patient encounters, thereby enabling automatic and real-time clinical documentation, which could significantly alleviate care clinicians’ burdens. Nevertheless, the performance of current-generation ASR technology in analyzing conversat...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: ce566a90-b3dc-52b5-8630-1ddb207ec6b2
DOI: 10.21203/rs.3.rs-4727659/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Assessing the Effectiveness of Automatic Speech Recognition Technology in Emergency Medicine Settings: A Comparative Study of Four AI-powered EnginesDOI 10.21203/rs.3.rs-4727659/v1Read

Clinical safety evaluation of ambient voice technologies in surgical documentationSemantic proximity Read

A Comparison of HIPAA-Compliant Transcription Services for Virtual Psychiatric InterviewsSemantic proximity Read

Automatic speech recognition alters diagnostic error and biomarker validity in AI-based dementia speech assessmentSemantic proximity Read

Ambient AI Documentation in Mixed-Language Encounters: A Heuristic Evaluation of Reenacted Mandarin–English and Spanish–English Clinical ConversationsSemantic proximity Read

A Clinical Speech Corpus with Temporally Aligned Sensitive Health InformationSemantic proximity Read

Implementing AI‑Powered Ambient Listening in Medication Reviews: Study Protocol and Pilot Evaluation in Belgian Community PharmaciesSemantic proximity Read

Evaluating Large Language Models for Drafting Emergency Department Discharge SummariesSemantic proximity Read

The Impact of Acoustic and Informational Noise on AI-Generated Clinical SummariesSemantic proximity Read

Automated speech analysis for risk detection of depression, anxiety, insomnia, and fatigue: Algorithm Development and Validation StudySemantic proximity Read

There’s not an APP for That: Comparing Interpretation Through an AI Voice App and Qualified Medical Interpreters in Real World Clinical SettingsSemantic proximity Read

AI-Powered Speech Therapy AssistantSemantic proximity Read

Impact of Ambient Artificial Intelligence Notes on Provider BurnoutSemantic proximity Read