Year: 2025
Type: article
Abstract: Recent advancements in voice-enabled artificial intelligence (AI), particularly end-to-end speech-to-speech models, are reshaping communication within health care. These models, such as OpenAI's Advanced Voice Mode (AVM), offer real-time, nuanced human-like interactions by capturing intonation and pitch, thereby enabling more natural machine-human dialogue. In this paper we explore the integration of voice-enabled AI into medical practice, highlighting the potential to improve clinical efficiency, medical education, and patient engagement by providing self-recorded use cases. While the benefits are promising-ranging from increased accessibility to reduced clinician workload-challenges remain in data security, reliability, integration with existing systems, and ethical use. Addressing these concerns through robust regulation, transparent development, and targeted training will be essential. Ultimately, voice-enabled AI holds transformative potential to bridge communication gaps in medicine and support more equitable, efficient, and patient-centered care.
Authors: C.M.L. Loeffler, H.S. Muti, J.N. Kather, D. Truhn
Institutions: Helmholtz-Zentrum Dresden-Rossendorf, University Hospital Carl Gustav Carus, Nationales Centrum für Tumorerkrankungen Dresden, Else Kröner Fresenius Center for Digital Health, Technische Universität Dresden, University Hospital Heidelberg, National Center for Tumor Diseases, Universitätsklinikum Aachen
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,170
OpenAlex ID: W4409917273