A systematic review of speech recognition technology in health care
Open accessAbstract
BACKGROUND: To undertake a systematic review of existing literature relating to speech recognition technology and its application within health care. METHODS: A systematic review of existing literature from 2000 was undertaken. Inclusion criteria were: all papers that referred to speech recognition (SR) in health care settings, used by health professionals (allied health, medicine, nursing, technical or support staff), with an evaluation or patient or staff outcomes. Experimental and non-experimental designs were considered. Six databases (Ebscohost including CINAHL, EMBASE, MEDLINE including the Cochrane Database of Systematic Reviews, OVID Technologies, PreMED-LINE, PsycINFO) were searched by a qualified health librarian trained in systematic review searches initially capturing 1,730 references. Fourteen studies met the inclusion criteria and were retained. RESULTS: The heterogeneity of the studies made comparative analysis and synthesis of the data challenging resulting in a narrative presentation of the results. SR, although not as accurate as human transcription, does deliver reduced turnaround times for reporting and cost-effective reporting, although equivocal evidence of improved workflow processes. CONCLUSIONS: SR systems have substantial benefits and should be considered in light of the cost and selection of the SR system, training requirements, length of the transcription task, potential use of macros and templates, the presence of accented voices or experienced and in-experienced typists, and workflow patterns.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Strategies to reduce documentation burden, including team documentation, automatic speech recognition technologies, and 2021 E&M coding changes have been implemented with variable impact.
“Strategies to reduce documentation burden, including team documentation, 9-13 automatic speech recognition technologies, 14 and 2021 E&M coding changes 15 have been implemented with variable impact.16”
From Ambient artificial intelligence scribes: utilization and impact on documentation time (2025) · cites this paper as [14]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Chaudhry, B., Wang, J., Wu, S., Maglione, M., Mojica, W., Roth, E., Morton, S. C., & Shekelle, P. G. (2006) · Annals of Internal Medicine · doi:10.7326/0003-4819-144-10-200605160-00125 · Cited by 3,159 · see citing works
Minimum prediction residual principle applied to speech recognition
Itakura, F. (1975) · IEEE Transactions on Acoustics Speech and Signal Processing · doi:10.1109/tassp.1975.1162641 · Cited by 1,620 · see citing works
Buntin, M. B., Burke, M. F., Hoaglin, M. C., & Blumenthal, D. (2011) · Health Affairs · doi:10.1377/hlthaff.2011.0178 · Cited by 1,311 · see citing works
Pluye, P., Gagnon, M.-P., Griffiths, F., & Johnson-Lafleur, J. (2009) · International Journal of Nursing Studies · doi:10.1016/j.ijnurstu.2009.01.009 · Cited by 1,119 · see citing works
Information Systems Development: Methodologies, Techniques and Tools
Avison, D., & Fitzgerald, G. (1995) · Cited by 1,055 · see citing works
New directions in eHealth communication: Opportunities and challenges
Kreps, G. L., & Neuhauser, L. (2010) · Patient Education and Counseling · doi:10.1016/j.pec.2010.01.013 · Cited by 546 · see citing works
Health Information Technology: An Updated Systematic Review With a Focus on Meaningful Use
Jones, S. S., Rudin, R. S., Perry, T., & Shekelle, P. G. (2014) · Annals of Internal Medicine · doi:10.7326/m13-1531 · Cited by 475 · see citing works
Costs And Benefits Of Health Information Technology: New Trends From The Literature
Goldzweig, C. L., Towfigh, A., Maglione, M., & Shekelle, P. (2009) · Health Affairs · doi:10.1377/hlthaff.28.2.w282 · Cited by 375 · see citing works
Jamal, A., McKenzie, K., & Clark, M. (2009) · Health Information Management Journal · doi:10.1177/183335830903800305 · Cited by 222 · see citing works
Pakhomov, S., Buntrock, J. D., & Chute, C. G. (2006) · Journal of the American Medical Informatics Association · doi:10.1197/jamia.m2077 · Cited by 161 · see citing works
Mendonça, E. A., Haas, J., Shagina, L., Larson, E., & Friedman, C. (2005) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2005.02.003 · Cited by 106 · see citing works
Devine, E. G., Gaehde, S. A., & Curtis, A. C. (2000) · Journal of the American Medical Informatics Association · doi:10.1136/jamia.2000.0070462 · Cited by 92 · see citing works
Zick, R. G., & Olsen, J. C. (2001) · The American Journal of Emergency Medicine · doi:10.1053/ajem.2001.24487 · Cited by 80 · see citing works
Alapetite, A., Andersen, H. B., & Hertzum, M. (2008) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2008.08.004 · Cited by 76 · see citing works
Comparison of Voice-Automated Transcription and Human Transcription in Generating Pathology Reports
Al-Aynati, M. M., & Chorneyko, K. A. (2003) · Archives of Pathology & Laboratory Medicine · doi:10.5858/2003-127-721-covtah · Cited by 69 · see citing works
Hospital Information Technology Systems' Impact on Nurses and Nursing Care
Waneka, R., & Spetz, J. (2010) · JONA: The Journal of Nursing Administration · doi:10.1097/nna.0b013e3181fc1a1c · Cited by 69 · see citing works
Improvement of Report Workflow and Productivity Using Speech Recognition—A Follow-up Study
Koivikko, M. P., Kauppinen, T., & Ahovuo, J. A. (2008) · Journal of Imaging Informatics in Medicine · doi:10.1007/s10278-008-9121-4 · Cited by 59 · see citing works
Speech Recognition as a Transcription Aid: A Randomized Comparison With Standard Transcription
Mohr, D. N., Turner, D. W., Pond, G. R., Kamath, J. S., Vos, C. B. D., & Carpenter, P. C. (2003) · Journal of the American Medical Informatics Association · doi:10.1197/jamia.m1130 · Cited by 53 · see citing works
Potential for Electronic Health Records and Online Social Networking to Redefine Medical Research
Pearson, J., Brownstein, C. A., & Brownstein, J. S. (2010) · Clinical Chemistry · doi:10.1373/clinchem.2010.148668 · Cited by 50 · see citing works
Impact of Speech Recognition on Radiologist Productivity
Langer, S. G. (2002) · Journal of Imaging Informatics in Medicine · doi:10.1007/s10278-002-0014-7 · Cited by 42 · see citing works
Voice Recognition Technology Implementation in Surgical Pathology: Advantages and Limitations
Singh, M., & Pal, T. R. (2011) · Archives of Pathology & Laboratory Medicine · doi:10.5858/arpa.2010-0714-oa · Cited by 39 · see citing works
Impact of noise and other factors on speech recognition in anaesthesia
Alapetite, A. (2006) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2006.11.007 · Cited by 38 · see citing works
Australasian Language Technology Association Workshop 2009
Pizzato, L. A. S., & Schwitter, R. (2009) · Cited by 34 · see citing works
Comparing nursing handover and documentation: forming one set of patient information
Johnson, M., Sanchez, P., Suominen, H., Basilakis, J., Dawson, L., Kelly, B., & Hanlen, L. (2013) · International Nursing Review · doi:10.1111/inr.12072 · Cited by 33 · see citing works
Self-citationInitial evaluation of a continuous speech recognition program for radiology
Kanal, K., Hangiandreou, N., Sykes, A., Eklund, H. E., Araoz, P., Leon, J., & Erickson, B. J. (2001) · Journal of Imaging Informatics in Medicine · doi:10.1007/s10278-001-0022-z · Cited by 32 · see citing works
Callaway, E. C., Sweet, C. F., Siegel, E. L., Reiser, J. M., & Beall, D. P. (2002) · Journal of Imaging Informatics in Medicine · doi:10.1007/bf03191902 · Cited by 28 · see citing works
Derman, Y. D., Arenovich, T., & Strauss, J. S. (2010) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-10-44 · Cited by 27 · see citing works
Experience with implementation of a radiology speech recognition system
Houston, J. D., & Rupp, F. W. (2000) · Journal of Imaging Informatics in Medicine · doi:10.1007/bf03168385 · Cited by 25 · see citing works
Dawson, L., Johnson, M., Suominen, H., Basilakis, J., Sanchez, P., Estival, D., Kelly, B. F., & Hanlen, L. (2014) · Journal of Medical Systems · doi:10.1007/s10916-014-0056-7 · Cited by 24 · see citing works
Self-citationFrom text to structured information
Hirschman, L., Grishman, R., & Sager, N. (1976) · AFIPS National Computer Conference and Exposition (NCC) · doi:10.1145/1499799.1499842 · Cited by 23 · see citing works
Mf, C. (1978) · PubMed · Cited by 23 · see citing works
Suominen, H. (2012) · CLEF (Online Working Notes/Labs/Workshop) · Cited by 15 · see citing works
Self-citationSpeech recognition in dental software systems: features and functionality.
Irwin, J. Y., Fernando, S., Schleyer, T., & Spallek, H. (2007) · PubMed · Cited by 12 · see citing works
Exploratory analysis of the medical record
Shapiro, A. R. (1983) · Medical Informatics · doi:10.3109/14639238309016080 · Cited by 9 · see citing works
Grammatical Compression in Notes and Records: Analysis and Computation
Anderson, B. B., & Sager, N. (1975) · Cited by 8 · see citing works
Automated analysis of the discharge summary.
Er, G., & Speth, D. J. (1986) · PubMed · Cited by 8 · see citing works
Relational data base modelling of free-text medical narrative
Chi, E. C., Sager, N., Tick, L. J., & Lyman, M. S. (1983) · Medical Informatics · doi:10.3109/14639238309016084 · Cited by 6 · see citing works
Language and the brain: Implications from new computer models
Young, D. A. (1982) · Medical Hypotheses · doi:10.1016/0306-9877(82)90066-4 · Cited by 5 · see citing works
Computerization of patho-histological findings in natural language.
Becker, H. (1972) · PubMed · Cited by 4 · see citing works
Suominen, H., & Ferraro, G. (2013) · ANU Open Research (Australian National University) · Cited by 3 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 1
- The pre-publication history for this paper can be accessed here: http://www.biomedcentral.com/1472-6947/14/94/prepub
Cited by
Sorted by citations
Velupillai, S. U., Suominen, H., Liakata, M., Roberts, A., Shah, A. D., Morley, K. I., Osborn, D., Hayes, J., Stewart, R. J., Downs, J. M., et al. (2018) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2018.10.005 · Cited by 253 · see citing works
Self-citationSpeech Technology for Healthcare: Opportunities, Challenges, and State of the Art
Latif, S., Qadir, J., Qayyum, A., Usama, M., & Younis, M. S. (2020) · IEEE Reviews in Biomedical Engineering · doi:10.1109/rbme.2020.3006860 · Cited by 177 · see citing works
Ambient artificial intelligence scribes: utilization and impact on documentation time
Ma, S. P., Liang, A. S., Shah, S. J., Smith, M., Jeong, Y., Devon-Sand, A., Crowell, T., Delahaie, C., Hsia, C., Lin, S., et al. (2025) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocae304 · Cited by 155 · see citing works
Javaid, M., Haleem, A., & Singh, R. P. (2024) · Informatics and Health · doi:10.1016/j.infoh.2024.05.001 · Cited by 121 · see citing works
Risks and benefits of speech recognition for clinical documentation: a systematic review
Hodgson, T., & Coiera, E. W. (2015) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocv152 · Cited by 108 · see citing works
Automatic documentation of professional health interactions: A systematic review
Falcetta, F. S., de Almeida, F. K., Lemos, J., Goldim, J. R., & da Costa, C. A. (2023) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2023.102487 · Cited by 98 · see citing works
Speech recognition for clinical documentation from 1990 to 2018: a systematic review
Blackley, S. V., Huynh, J., Wang, L., Korach, Z., & Zhou, L. (2019) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocy179 · Cited by 97 · see citing works
Zhou, L., Blackley, S. V., Kowalski, L., Doan, R., Acker, W. W., Landman, A. B., Kontrient, E., Mack, D., Meteer, M., Bates, D. W., et al. (2018) · JAMA Network Open · doi:10.1001/jamanetworkopen.2018.0530 · Cited by 94 · see citing works
Almarzouqi, A., Aburayya, A., & Salloum, S. A. (2022) · PLoS ONE · doi:10.1371/journal.pone.0272735 · Cited by 91 · see citing works
Blackley, S. V., Schubert, V. D., Goss, F. R., Assad, W. A., Garabedian, P. M., & Zhou, L. (2020) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2020.104178 · Cited by 70 · see citing works
Zhang, J., Wu, J., Qiu, Y., Song, A., Li, W., Li, X., & Liu, Y. (2023) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2022.106517 · Cited by 69 · see citing works
Proof of Concept of an Assistive Robotic Arm Control Using Artificial Stereovision and Eye-Tracking
Cio, Y.-S. L.-K., Raison, M., Leblond-Ménard, C., & Achiche, S. (2019) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2019.2950619 · Cited by 65 · see citing works
Suominen, H., Zhou, L., Hanlen, L., & Ferraro, G. (2015) · JMIR Medical Informatics · doi:10.2196/medinform.4321 · Cited by 58 · see citing works
Self-citationDigitization of Pathology Labs: A Review of Lessons Learned
Schwen, L. O., Kiehl, T., Carvalho, R., Zerbe, N., & Homeyer, A. (2023) · Laboratory Investigation · doi:10.1016/j.labinv.2023.100244 · Cited by 55 · see citing works
Joseph, J., Moore, Z. E. H., Patton, D., O'Connor, T., & Nugent, L. E. (2020) · Journal of Clinical Nursing · doi:10.1111/jocn.15261 · Cited by 49 · see citing works
Learning to Detect Dysarthria from Raw Speech
Millet, J., & Zeghidour, N. (2019) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2019.8682324 · Cited by 49 · see citing works
Kovalchuk, S. V., Kopanitsa, G., Derevitskii, I. V., Matveev, G. A., & Savitskaya, D. A. (2022) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2022.104013 · Cited by 48 · see citing works
Vogel, M., Kaisers, W., Waßmuth, R., & Mayatepek, E. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.5072 · Cited by 42 · see citing works
A dataset of simulated patient-physician medical interviews with a focus on respiratory cases
Fareez, F., Parikh, T., Wavell, C., Shahab, S., Chevalier, M., Good, S., De Blasi, I., Rhouma, R., McMahon, C., Lam, J.-P., et al. (2022) · Scientific Data · doi:10.1038/s41597-022-01423-1 · Cited by 39 · see citing works
Kumar, Y., Koul, A., & Mahajan, S. (2022) · Soft Computing · doi:10.1007/s00500-022-07261-y · Cited by 35 · see citing works
Speech Recognition for Medical Dictation: Overview in Quebec and Systematic Review
Poder, T. G., Fisette, J., & Déry, V. (2018) · Journal of Medical Systems · doi:10.1007/s10916-018-0947-0 · Cited by 30 · see citing works
Yang, L. W. Y., Ng, W. Y., Foo, L. L., Liu, Y., Yan, M., Lei, X., Zhang, X., & Ting, D. S. W. (2021) · Current Opinion in Ophthalmology · doi:10.1097/icu.0000000000000789 · Cited by 28 · see citing works
Nguyen, O. T., Turner, K. L., Apathy, N. C., Magoč, T., Hanna, K., Merlo, L. J., Harle, C. A., Thompson, L. A., Berner, E. S., & Feldman, S. S. (2021) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocab272 · Cited by 28 · see citing works
Words prediction based on N-gram model for free-text entry in electronic health records
Yazdani, A., Safdari, R., Golkar, A., & Kalhori, S. R. N. (2019) · Health Information Science and Systems · doi:10.1007/s13755-019-0065-5 · Cited by 28 · see citing works
Deep Learning for Punctuation Restoration in Medical Reports
Salloum, W., Finley, G. P., Edwards, E., Miller, M., & Suendermann‐Oeft, D. (2017) · doi:10.18653/v1/w17-2319 · Cited by 27 · see citing works
Dinari, F., Bahaadinbeigy, K., Bassiri, S., Mashouf, E., Bastaminejad, S., & Moulaei, K. (2023) · Health Science Reports · doi:10.1002/hsr2.1330 · Cited by 26 · see citing works
Zuchowski, M. L., & Göller, A. (2022) · British Journal of Healthcare Management · doi:10.12968/bjhc.2021.0074 · Cited by 25 · see citing works
Seyedi, S. S., Griner, E. L., Corbin, L., Jiang, Z., Roberts, K., Iacobelli, L., Milloy, A., Boazak, M., Rad, A. B., Abbasi, A., et al. (2023) · JMIR Mental Health · doi:10.2196/48517 · Cited by 25 · see citing works
Development and Application of Artificial Intelligence in Auxiliary TCM Diagnosis
Feng, C., Shao, Y., Wang, B., Qu, Y., Wang, Q., Li, Y., & Yang, T. (2021) · Evidence-based Complementary and Alternative Medicine · doi:10.1155/2021/6656053 · Cited by 24 · see citing works
PriMock57: A Dataset Of Primary Care Mock Consultations
Papadopoulos Korfiatis, A., Moramarco, F., Sarac, R., & Savkov, A. (2022) · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) · doi:10.18653/v1/2022.acl-short.65 · Cited by 23 · see citing works
Computational intelligence in processing of speech acoustics: a survey
Singh, A., Kaur, N., Kukreja, V., Kadyan, V., & Kumar, M. (2022) · Complex & Intelligent Systems · doi:10.1007/s40747-022-00665-1 · Cited by 23 · see citing works
Peivandi, S., Ahmadian, L., Farokhzadian, J., & Jahani, Y. (2022) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-022-01835-4 · Cited by 23 · see citing works
Farzandipour, M., Meidani, Z., Riazi, H., & Jabali, M. S. (2017) · Informatics for Health and Social Care · doi:10.1080/17538157.2017.1290639 · Cited by 22 · see citing works
The technological imperative for value-based health care
Meinert, E., Alturkistani, A., Brindley, D. A., Knight, P., Wells, G., & de Pennington, N. (2018) · British Journal of Hospital Medicine · doi:10.12968/hmed.2018.79.6.328 · Cited by 22 · see citing works
Onitilo, A. A., Shour, A. R., Puthoff, D. S., Tanimu, Y., Joseph, A., & Sheehan, M. T. (2023) · PLOS ONE · doi:10.1371/journal.pone.0272545 · Cited by 21 · see citing works
Saxena, K., Diamond, R., Conant, R., Mitchell, T. H., Gallopyn, G., & Yakimow, K. E. (2018) · Europe PMC (PubMed Central) · Cited by 19 · see citing works
Bai, J. (2022) · Computational Intelligence and Neuroscience · doi:10.1155/2022/5066004 · Cited by 17 · see citing works
Machine learning-based speech recognition system for nursing documentation – A pilot study
Lee, T., Li, C.-C., Chou, K., Chung, M., Hsiao, S.-T. S., Guo, S.-L., Hung, L.-Y., & Wu, H. (2023) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2023.105213 · Cited by 16 · see citing works
Social influence-based contrast language analysis framework for clinical decision support systems
Yang, X., Joukova, A., Ayanso, A., & Zihayat, M. (2022) · Decision Support Systems · doi:10.1016/j.dss.2022.113813 · Cited by 16 · see citing works
Hou, S.-Y., Wu, Y.-L., Chen, K.-C., Chang, T.-A., Hsu, Y.-M., Chuang, S.-J., Chang, Y., & Hsu, K.-C. (2022) · JMIR Nursing · doi:10.2196/37562 · Cited by 15 · see citing works
Lee, S. H., Park, J., Yang, K., Min, J., & Choi, J. (2022) · Journal of Korean Medical Science · doi:10.3346/jkms.2022.37.e144 · Cited by 15 · see citing works
Artificial Intelligence Technology and Engineering Applications
Li, X., & Jiang, H. (2017) · The Applied Computational Electromagnetics Society Journal (ACES) · Cited by 15 · see citing works
Mobile payment recognition technology based on face detection algorithm
Du, M. (2018) · Concurrency and Computation Practice and Experience · doi:10.1002/cpe.4655 · Cited by 14 · see citing works
An ultralow-crosstalk wearable piezoelectric sensing system for voiced and silent speech decoding
Yu, L., Zhen, L., Cui, M., Chen, X., Bai, X., Shao, Y., & Yang, B. T. (2025) · Chemical Engineering Journal · doi:10.1016/j.cej.2025.168111 · Cited by 12 · see citing works
Harrington, L. (2023) · Frontiers in Communication · doi:10.3389/fcomm.2023.1165233 · Cited by 12 · see citing works
Fogleman, B. M., Goldman, M., Holland, A. B., Dyess, G. A., & Patel, A. (2024) · Cureus · doi:10.7759/cureus.58032 · Cited by 12 · see citing works
Speech technology in healthcare
Deepa, P., & Khilar, R. (2022) · Measurement Sensors · doi:10.1016/j.measen.2022.100565 · Cited by 12 · see citing works
From dictations to clinical reports using machine translation
Finley, G. P., Salloum, W., Sadoughi, N., Edwards, E., Robinson, A., Axtmann, N., Brenndoerfer, M., Miller, M., & Suendermann‐Oeft, D. (2018) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.18653/v1/n18-3015 · Cited by 12 · see citing works
Automatic voice emotion recognition of child-parent conversations in natural settings
Law, E. L., Soleimani, S., Watkins, D., & Barwick, J. (2020) · Behaviour and Information Technology · doi:10.1080/0144929x.2020.1741684 · Cited by 12 · see citing works
Task 1a of the CLEF eHealth Evaluation Lab 2015: Clinical Speech Recognition
Suominen, H., Hanlen, L., Goeuriot, L., Kelly, L., & Jones, G. J. F. (2015) · HAL · Cited by 11 · see citing works
Self-citationCrowdsourced Continuous Improvement of Medical Speech Recognition.
Salloum, W., Edwards, E., Ghaffarzadegan, S., Suendermann‐Oeft, D., & Miller, M. A. (2017) · National Conference on Artificial Intelligence · Cited by 11 · see citing works
Physician experience with speech recognition software in psychiatry: usage and perspective
Fernandes, J., Brunton, I., Strudwick, G., Banik, S., & Strauss, J. (2018) · BMC Research Notes · doi:10.1186/s13104-018-3790-y · Cited by 11 · see citing works
Xie, T. (2023) · Soft Computing · doi:10.1007/s00500-023-08147-3 · Cited by 10 · see citing works
Retracted[Solution] IPA: Inference Pipeline Adaptation to achieve high accuracy and cost-efficiency
Ghafouri, S., Razavi, K., Salmani, M., Sanaee, A., Lorido-Botrán, T., Wang, L., Doyle, J., & Jamshidi, P. (2024) · Journal of Systems Research · doi:10.5070/sr34163500 · Cited by 10 · see citing works
Introduction of digital speech recognition in a specialised outpatient department: a case study
Ahlgrim, C., Maenner, O., & Baumstark, M. W. (2016) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-016-0374-4 · Cited by 10 · see citing works
New report preparation system for endoscopic procedures using speech recognition technology
Takao, T., Masumura, R., Sakauchi, S., Ohara, Y., Bilgiç, E., Umegaki, E., Kutsumi, H., & Azuma, T. (2018) · Endoscopy International Open · doi:10.1055/a-0579-6494 · Cited by 10 · see citing works
Speech recognition technology in prehospital documentation: A scoping review
Hedderson, D., Courtney, K. L., Monkman, H., & Blanchard, I. E. (2024) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2024.105662 · Cited by 9 · see citing works
Design of Political Online Teaching Based on Artificial Speech Recognition and Deep Learning
Chen, X. (2022) · Computational Intelligence and Neuroscience · doi:10.1155/2022/3112092 · Cited by 8 · see citing works
Chun, S.-J., Park, J., Ryu, H., & Jang, B. (2023) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2023.105112 · Cited by 8 · see citing works
Bock, A., Elvers, D., Goloborodko, E., Kramer, C., Kniha, K., Hölzle, F., Spreckelsen, C., & Modabber, A. (2020) · Oral Surgery Oral Medicine Oral Pathology and Oral Radiology · doi:10.1016/j.oooo.2020.10.002 · Cited by 8 · see citing works
A video indexing and retrieval computational prototype based on transcribed speech
Spolaôr, N., Lee, H., Takaki, W. S. R., Ensina, L. A., Parmezan, A. R. S., Oliva, J. T., Coy, C. S. R., & Wu, F. C. (2021) · Multimedia Tools and Applications · doi:10.1007/s11042-021-11401-1 · Cited by 7 · see citing works
Automatic illness prediction system through speech
Abdulmohsin, H. A., Al‐Khateeb, B., Hasan, S. S., & Dwivedi, R. (2022) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2022.108224 · Cited by 7 · see citing works
A Randomized Trial of Voice-Generated Inpatient Progress Notes: Effects on Professional Fee Billing
White, A. A., Lee, T., Garrison, M. M., & Payne, T. H. (2020) · Applied Clinical Informatics · doi:10.1055/s-0040-1713134 · Cited by 7 · see citing works
Asynchronous Speech Recognition Affects Physician Editing of Notes
Lybarger, K., Mari Ostendorf, E., Riskin, E. A., Payne, T. H., White, A. A., & Yetişgen, M. (2018) · Applied Clinical Informatics · doi:10.1055/s-0038-1673417 · Cited by 6 · see citing works
Automatic speech recognition for Indonesian medical dictation in cloud environment
Jarin, A., Santosa, A., Uliniansyah, M. T., Aini, L. R., Nurfadhilah, E., & Gunarso, G. (2024) · IAES International Journal of Artificial Intelligence · doi:10.11591/ijai.v13.i2.pp1762-1772 · Cited by 6 · see citing works
Self-Training and Error Correction using Large Language Models for Medical Speech Recognition
Dungavath, S. N., Nataraj, K. S., & Tiwari, N. (2024) · IEEE Conference on Engineering Informatics (ICEI) · doi:10.1109/icei64305.2024.10912300 · Cited by 5 · see citing works
Atiku, S. O., Owolanke, K., & Olakotan, O. O. (2026) · Journal of Evaluation in Clinical Practice · doi:10.1111/jep.70460 · Cited by 5 · see citing works
Ahamed, S., Weiler, G., Boden, K., Januschowski, K., Stennes, M., McCrae, P., Bock, C., Rawein, C., Petris, M. D., Foth, K. A., et al. (2021) · Studies in health technology and informatics · doi:10.3233/shti210121 · Cited by 5 · see citing works
Central Kurdish Automatic Speech Recognition using Deep Learning
Abdullah, A. A., & Veisi, H. (2022) · Journal of university of Anbar for pure science · doi:10.37652/juaps.2022.176500 · Cited by 5 · see citing works
Vazquez, M. F. A., Rupp, N., Ballardt, L., Opara, J., & Züchner, T. (2023) · Scientific Reports · doi:10.1038/s41598-023-46185-x · Cited by 5 · see citing works
Synthetic AI Data Pipeline for Domain-Specific Speech-to-Text Solutions
Karl, A. L., Fernandes, G. S., Pires, L. A., Serpa, Y. R., & Caminha, C. (2024) · Simpósio Brasileiro de Tecnologia da Informação e da Linguagem Humana (STIL) · doi:10.5753/stil.2024.245336 · Cited by 5 · see citing works
Zeeshan, R., Bogue, J., & Asghar, M. N. (2025) · IEEE Access · doi:10.1109/access.2025.3585454 · Cited by 5 · see citing works
Tang, L. A., Johnson, K. B., & Kumah-Crystal, Y. A. (2018) · Europe PMC (PubMed Central) · Cited by 5 · see citing works
Creating Custom Digital Assistants for the Scientific Laboratory using the HelixAI Platform
Rhodes, D. V. L., & Rhodes, J. G. (2022) · SLAS TECHNOLOGY · doi:10.1016/j.slast.2022.05.002 · Cited by 4 · see citing works
Speech Recognition System Generates Highly Accurate Endoscopic Reports in Clinical Practice
Takayama, H., Takao, T., Masumura, R., Yamaguchi, Y., Yonezawa, R., Sakaguchi, H., Morita, Y., Toyonaga, T., Izumiyama, K., & Kodama, Y. (2022) · Internal Medicine · doi:10.2169/internalmedicine.9592-22 · Cited by 4 · see citing works
Evaluation Data and Benchmarks for Cascaded Speech Recognition and Entity Extraction
Zhou, L., Suominen, H., & Hanlen, L. (2015) · doi:10.1145/2802558.2814646 · Cited by 4 · see citing works
Self-citationWang, M. (2024) · Measurement Sensors · doi:10.1016/j.measen.2023.101017 · Cited by 4 · see citing works
Li, L., Wang, G., & Freeman, G. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713124 · Cited by 3 · see citing works
Elsayed, N. (2026) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2026.106419 · Cited by 3 · see citing works
Vidal‐Alaball, J., Alonso, C. V., Heinisch, D. H., Castaño, A., Sánchez-Freire, E., Serrano, M. L. B., Pascual, C. F., Menacho, I., Acosta‐Rojas, R., Gubert, O. C., et al. (2025) · JMIR Research Protocols · doi:10.2196/66232 · Cited by 3 · see citing works
Computer audition for healthcare: A survey on speech analysis
Qian, K., Zhao, Z., Tan, Y., Zhang, W., Cho, M., Zhu, C., Tian, F., Hu, B., Yamamoto, Y., & Schuller, B. W. (2025) · AI Open · doi:10.1016/j.aiopen.2025.10.001 · Cited by 3 · see citing works
Speech Technology in Dutch Health Care: A Qualitative Study
Luchies, E., Spruit, M. R., & Askari, M. (2018) · International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC) · doi:10.5220/0006550103390348 · Cited by 3 · see citing works
Term-Based Personalization for Feature Selection in Clinical Handover Form Auto-Filling
Liu, H., Hu, Q., & He, L. (2018) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2018.2874237 · Cited by 3 · see citing works
Lo, B., Almilaji, K., Jankowicz, D., Sequeira, L., Strudwick, G., & Tajirian, T. (2021) · PubMed Central · Cited by 3 · see citing works
“Alexa, Cycle The Blood Pressure”: A Voice Control Interface Method for Anesthesia Monitoring
Lee, G., & Connor, C. W. (2024) · Anesthesia & Analgesia · doi:10.1213/ane.0000000000007003 · Cited by 2 · see citing works
Wojda, T. R., Savio, F. V. D., Hochheiser, H., Amaravathi, A., Bharat, K. T., & Fischer, G. M. (2025) · Artificial intelligence · doi:10.5772/intechopen.1011340 · Cited by 2 · see citing works
The Development of Northern Thai Dialect Speech Recognition System
Bootkrajang, J., Inkeaw, P., Chaijaruwanich, J., Taerungruang, S., Boonyawisit, A., Sutawong, B. J. M., Chunwijitra, V., & Taninpong, P. (2025) · Applied Sciences · doi:10.3390/app16010160 · Cited by 2 · see citing works
Improved efficiency of patient admission with electronic health records in neurosurgery
Polanski, W. H., Danker, A., Zolal, A., Senf-Mothes, D., Schackert, G., & Krex, D. (2020) · Health Information Management Journal · doi:10.1177/1833358320920990 · Cited by 2 · see citing works
Minerbi, A., Besemann, M., Kari, T., Gentile, C., & Gupta, G. (2020) · Military Medicine · doi:10.1093/milmed/usz374 · Cited by 2 · see citing works
Zhang, T. (2023) · International Journal of Systems Assurance Engineering and Management · doi:10.1007/s13198-023-02003-1 · Cited by 2 · see citing works
Asli, P. A., & Zumbansen, A. (2023) · IEEE International Symposium on Medical Measurements and Applications (MeMeA) · doi:10.1109/memea57477.2023.10171898 · Cited by 2 · see citing works
Evaluating and Improving Automatic Speech Recognition using Severity
Whetten, R., & Kennington, C. (2023) · Workshop on Biomedical Language Processing (BioNLP) · doi:10.18653/v1/2023.bionlp-1.6 · Cited by 2 · see citing works
Review of Discrete Wavelet Transform-Based Emotion Recognition from Speech
Anand, A., Nambiar, A., Pani, S., & Mohanaprasad, K. (2023) · Lecture notes in electrical engineering · doi:10.1007/978-981-19-8338-2_3 · Cited by 2 · see citing works
Health Informatics and Data Migration Integrity Nexus: Implications, Challenges and Solutions
Lawanson, M. O. L. M. O., Abuhalimeh, A., Ajiferuke, O., & Olayinka, L. T. (2025) · doi:10.38124/ijisrt/25jul763 · Cited by 2 · see citing works
Information Extraction to Improve Standard Compliance
Zhou, L., & Suominen, H. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-26350-2_57 · Cited by 2 · see citing works
Self-citationFemi-Abodunde, A., Olinger, K., Burke, L. M. B., Benefield, T., Lee, E. R., McGinty, K., & Mervak, B. M. (2021) · Journal of Imaging Informatics in Medicine · doi:10.1007/s10278-021-00502-w · Cited by 2 · see citing works
Capturing Talk: The Institutional Practices Surrounding the Transcription of Spoken Language
(2024) · Frontiers research topics · doi:10.3389/978-2-8325-4933-9 · Cited by 2 · see citing works
Learning representations of speech from the raw waveform
Zeghidour, N. (2019) · theses.fr (ABES) · doi:10.70675/2d69ced4z8cd6z40f9z996dzacc325ed994f · Cited by 2 · see citing works
AN ELECTRONIC PRESCRIBING SYSTEM FOR TELECONSULTATION USING HEALTHCARE 5.0 INNOVATIONS
AL-anazi, R. G., Singla, C., Alzaidi, M. S. A., Alamgeer, M., ASKLANY, S. A., TANEJA, N., ALMUKADI, W. S., & MOHAMED, A. A. (2024) · Fractals · doi:10.1142/s0218348x25400559 · Cited by 1 · see citing works
Lo, Y.-J., Chang, Y., Chen, C., Wang, H.-P., Wang, H., Ohiro, Y., & Fang, C.-Y. (2025) · Journal of Dental Sciences · doi:10.1016/j.jds.2025.10.034 · Cited by 1 · see citing works
- Authors
- Johnson, M., Lapkin, S., Long, V., Sanchez, P., Suominen, H., Basilakis, J., & Dawson, L.
- Affiliations
- Ingham Institute (AU)
- Western Sydney University (AU)
- Australian National University (AU)
- University of Wollongong (AU)
- Corresponding author
- Johnson, Maree
- Venue
- BMC Medical Informatics and Decision Making
- Published
- 2014-10-28
- Volume
- 14
- Issue
- 1
- Pages
- 94-94
- ISSN
- 1472-6947 (ISSN-L)
- PMC
- PMC4283090
- OpenAlex
- W2046499381
- Cited by
- 141
- References
- 40
- Citations by year
- 2026: 13 · 2025: 17 · 2024: 16 · 2023: 23 · 2022: 18 · 2021: 8 · 2020: 11 · 2019: 7 · 2018: 16 · 2017: 4 · 2016: 2 · 2015: 6
- FWCI
- 0.61
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Medical Informatics and Decision Making (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research Bank (Australian Catholic University) (submittedVersion)
- Research Online (University of Wollongong) (submittedVersion)
- Figshare (submittedVersion)
- ANU Open Research (Australian National University) (submittedVersion, cc-by)
- Funders
- ACT Government
- Australian Government
- Australian National University
- University of New South Wales
- University of Sydney
- University of Western Sydney
- Monash University
- University of Melbourne
- Griffith University
- Queensland University of Technology
- University of Queensland
- Australian Research Council
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
- Health Sciences › Nursing › Issues, ethics and legal aspects › Nursing Diagnosis and Documentation
- Keywords
- speech recognition, clinical documentation, transcription, cost-effectiveness, speech recognition accuracy, voice recognition
- MeSH terms
- Health Services, Humans, Speech Recognition Software
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
