The DOI matches its Crossref record; 207 of the 220 references it cites were found in a registry or an index.
Intelligent speech technologies for transcription, disease diagnosis, and medical equipment interactive control in smart hospitals: A review
Open accessAbstract
The growing and aging of the world population have driven the shortage of medical resources in recent years, especially during the COVID-19 pandemic. Fortunately, the rapid development of robotics and artificial intelligence technologies help to adapt to the challenges in the healthcare field. Among them, intelligent speech technology (IST) has served doctors and patients to improve the efficiency of medical behavior and alleviate the medical burden. However, problems like noise interference in complex medical scenarios and pronunciation differences between patients and healthy people hamper the broad application of IST in hospitals. In recent years, technologies such as machine learning have developed rapidly in intelligent speech recognition, which is expected to solve these problems. This paper first introduces IST's procedure and system architecture and analyzes its application in medical scenarios. Secondly, we review existing IST applications in smart hospitals in detail, including electronic medical documentation, disease diagnosis and evaluation, and human-medical equipment interaction. In addition, we elaborate on an application case of IST in the early recognition, diagnosis, rehabilitation training, evaluation, and daily care of stroke patients. Finally, we discuss IST's limitations, challenges, and future directions in the medical field. Furthermore, we propose a novel medical voice analysis system architecture that employs active hardware, active software, and human-computer interaction to realize intelligent and evolvable speech recognition. This comprehensive review and the proposed architecture offer directions for future studies on IST and its applications in smart hospitals.
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“Functions such as reminders (Hellwig et al., 2018;Malapaschas, 2021), Smart Home applications, infotainment, communication (calls and messages; Hellwig et al., 2018), health documentation (Hellwig et al., 2018;Zhang et al., 2023), and managing shopping, to-do lists (Pradhan et al., 2018), or structuring the day (Kopp et al., 2018) can optimize the quality of life of people with physical, cognitive”
From Use and acceptance of voice assistants among people with aphasia in Germany (2023) · cites this paper as Zhang et al., 2023
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“At the same time, the workload of caregivers and medical staff can be reduced (Hellwig et al., 2018;Zhang et al., 2023).”
From Use and acceptance of voice assistants among people with aphasia in Germany (2023) · cites this paper as Zhang et al., 2023
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Kooli, C., & CHAKRAOUI, R. (2025) · Sustainable Futures · doi:10.1016/j.sftr.2025.101042 · Cited by 91
Eftekhari, H. (2024) · European Journal of Cardiovascular Nursing · doi:10.1093/eurjcn/zvae013 · Cited by 72
Mohammad‐Rahimi, H., Sohrabniya, F., Ourang, S. A., Dianat, O., Aminoshariae, A., Nagendrababu, V., Dummer, P. M. H., Duncan, H. F., & Nosrat, A. (2024) · International Endodontic Journal · doi:10.1111/iej.14128 · Cited by 74
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Metadata
- Authors
- Zhang, J., Wu, J., Qiu, Y., Song, A., Li, W., Li, X., & Liu, Y.
- Affiliations
- State Key Laboratory of Digital Medical Engineering (CN)
- Guangdong Academy of Medical Sciences (CN)
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Corresponding author
- Zhang, Jun
- Venue
- Computers in Biology and Medicine
- Publisher
- Elsevier BV
- Published
- 2023-02
- Volume
- 153
- Pages
- 106517
- ISSN
- 0010-4825 (ISSN-L)
- PMC
- PMC9814440
- OpenAlex
- W4313561446
- Cited by
- 69
- References
- 220
- Citations by year
- 2026: 15 · 2025: 24 · 2024: 20 · 2023: 10
- FWCI
- 1.44
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- Computers in Biology and Medicine (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Key Research and Development Program of China (2020AAA0109603)
- National Natural Science Foundation of China (61873066, 62173090)
- Ministry of Science and Technology of the People's Republic of China
- Southeast University (2242020R40096)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
- Health Sciences › Health Professions › Speech and Hearing › Voice and Speech Disorders
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Keywords
- speech recognition, smart hospitals, disease diagnosis, human-machine interaction, stroke rehabilitation, noise interference, pronunciation differences, medical robotics
- MeSH terms
- COVID-19, COVID-19 Testing, Artificial Intelligence, Humans, Robotics, Speech, Pandemics
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