Medical transcription is the process of conversion of audio files, dictated by medical experts, to electronic
data files in a predetermined format. The doctor ‘s thoughts are documented, covering medical procedures carried
out on a patient starting from the time the patient enters the clinic or hospital, up until the ailment is treated.
A grammar checker is an important asset to hospitals to scrutinize medical transcripts. The transcripts are important
to track a patient’s medical history and need to be error free. The available existing tools are specifically designed to
detect faulty grammatical constructs in the generic English language. It is important to improve the intelligence of a
grammar checker in a relatively unknown domain and to improve the level of accuracy set by the existing tools which
mostly rely on a set of non-exhaustive rulesets. These are the driving factors to propose a new approach to an old
problem. Stop words are most commonly occurring words in any language. By exploiting the fact that stop words
form the backbone of a sentence and by figuring out the common parts-of-speech tags which surround them,
a sentence’s grammatical structure can be better understood using statistical methods.
G. B. R., Dr. Deepa Gupta, and Sasikala T, “Grammar Error Detection Tool for Medical Transcription using Stop Words – POS Tags ngram Based Model ”, in 2nd International Conference on Computational Intelligence and Informatics(ICCI’17), JNTU, Hyderabad , 2017.