Models trained on noisy sentences from plan-headed sections in clinical notes reach F-measures of 0.91-0.97 for identifying treatment plan sentences.
Section classification in clinical notes using supervised hidden markov model
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Training Models to Extract Treatment Plans from Clinical Notes Using Contents of Sections with Headings
Models trained on noisy sentences from plan-headed sections in clinical notes reach F-measures of 0.91-0.97 for identifying treatment plan sentences.