Computerized radiologic reporting with voice data-entry.

Leeming, B. W. A.; Porter, David; Jackson, J D; Bleich, Howard L.; Simón, M.

doi:10.1148/radiology.138.3.7465833

Cited by 44 publications

(21 citation statements)

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“…C omputerized voice recognition (VR) for radiology reporting was first described in 1981, 1 and had remained more or less a novelty in the following two decades. Early systems were hampered by limited vocabularies and required 3 to 6 h training sessions before the system recognized the user's voice.…”

Section: Introductionmentioning

confidence: 99%

Voice Recognition Dictation: Radiologist as Transcriptionist

et al. 2007

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Section: Introductionmentioning

confidence: 99%

Voice Recognition Dictation: Radiologist as Transcriptionist

et al. 2007

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“…Since the first attempts at computer-aided processing of radiographic reports in the late 1960 s [2,4], various reporting systems have been developed and used in several hospitals for writing and compiling reports [5,6]. Compared with conventional dictation processing, however, several drawbacks were recognized [7].…”

Section: Discussionmentioning

confidence: 99%

A computer-based reporting system in radiology of the chest

et al. 1998

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The aim of this study was to compare our computer-aided report writing system to standard techniques. A computer-aided reporting system for reporting on chest X-rays was developed and linked with a UNIX-based radiology information system. The reporting system consists of different text modules which can be composed to a complete radiological report. The quality of the report, the system's efficiency, flexibility and availability at the radiology information system (RIS), as well as its acceptance by the users, were criteria we took as a basis of evaluation. Acceptance and flexibility of the system were tested by assessing necessary changes and additions performed to text modules and by subjective evaluation. The time spent on working with the reporting system was evaluated by performing a time-analysis study comparing the new system to the two conventional methods, the tape system and handwriting. On average, the readers needed 22.6 text modules for each report. For the users the most important advantages of the new system are that primarily fewer changes to or additions to the text are necessary, and when they cannot be avoided they can be performed more easily. In comparison with the tape system and handwritten reports, it took on average two and a half to three times longer to report on a chest X-ray. The printed report had left the department within 6.4 h using the tape system within 0.4 h when handwritten and within 1.4 h when recorded by the reporting system. The completeness of the set of modules and the logical order were positively assessed by the users. The demand of time for reporting increases, but the final report is available sooner.

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“…The use of computerised voice recognition in medicine was first described in radiology in 1981. 3 In early studies the higher error rate of digital transcription when compared with traditional typing was highlighted. The main reasons for the high error rate then were the necessity to speak each word distinctly in a monotonous voice in order for the computer to recognise it.…”

Section: Voice Recognition In Healthcarementioning

confidence: 99%

Voice recognition software: psychiatrist as transcriber

Sandilyan¹,

Darley²

2013

Psychiatrist

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Continuous voice recognition software or speech recognition software (also known as automatic speech recognition, computer speech recognition, speech to text, or just STT) converts spoken words into text. The term 'voice recognition' is used to refer to systems that must be trained to a particular speaker and are commonly used in healthcare settings to replace or improve the efficiency of medical transcribers (usually medical secretaries). Early systems required the speaker to pause between each word, were slow, and had limited vocabulary and high error rates. Recent advances in this field have generated newer systems that understand continuous speech, run on common personal computers and produce more accurate results. 1Voice recognition systems comprise a microphone that converts speech to an analogue electrical signal, which is converted to a digital signal by an electronic circuit board within a computer. 2 Speech recognition engine software then uses acoustic, language and vocabulary models as well as complex statistical algorithms to transform the digital signal into words and punctuation marks. The acoustic model removes noise and unnecessary information such as changes in volume. The language model then analyses the content of the speech; it compares the combinations of phonemes with the words in its digital dictionary, a huge database of the most common words in the English language. Most of today's packages come with dictionaries containing about 150 000 words. The language model quickly decides which words were said and displays them on the screen. The commercial software package used for this study is widely used in UK healthcare within National Health Service (NHS) trusts and general practices to produce clinical correspondence using digital dictation and transcription (similar software packages are available in other countries). It includes a wide selection of medical terms and comes with a 'training wizard' which learns new words and also adapts itself to the voice of a new user. The software has wide applications in commercial settings, for example in automated telephone messaging services, which have a limited vocabulary for a wide range of users; other applications of voice recognition may have a large vocabulary trained to work best with a small number of users, such as in digital transcription services. Voice recognition in healthcareThere is a huge pressure in healthcare settings to generate large amounts of documentation in a short time. The use of computerised voice recognition in medicine was first described in radiology in 1981.3 In early studies the higher error rate of digital transcription when compared with traditional typing was highlighted. The main reasons for the high error rate then were the necessity to speak each word distinctly in a monotonous voice in order for the computer to recognise it. This also resulted in the doctor spending more time in correcting errors as they appeared on the screen in real time. Things have changed over the years in that newer software is able to r...

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Computerized radiologic reporting with voice data-entry.

Cited by 44 publications

References 0 publications

Voice Recognition Dictation: Radiologist as Transcriptionist

Voice Recognition Dictation: Radiologist as Transcriptionist

A computer-based reporting system in radiology of the chest

Voice recognition software: psychiatrist as transcriber

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