Readability Evaluation for Ukrainian Medicine Corpus(UKRMED)
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[1] David Kauchak,et al. NegAIT: A new parser for medical text simplification using morphological, sentential and double negation , 2017, J. Biomed. Informatics.
[2] Maha Al-Yahya,et al. Readability of Arabic Medicine Information Leaflets: A Machine Learning Approach , 2016, Procedia Computer Science.
[3] Olga Cherednichenko,et al. Collection and Processing of a Medical Corpus in Ukrainian , 2020, COLINS.
[4] Laurie Hoffman-Goetz,et al. What is consumer health informatics? A systematic review of published definitions , 2015, Informatics for health & social care.
[5] Lucia Specia,et al. Text Simplification from Professionally Produced Corpora , 2018, LREC.
[6] David Kauchak,et al. Moving Beyond Readability Metrics for Health-Related Text Simplification , 2016, IT Professional.
[7] H. T. Kung,et al. Language Modeling by Clustering with Word Embeddings for Text Readability Assessment , 2017, CIKM.
[8] Gondy Leroy,et al. The influence of text characteristics on perceived and actual difficulty of health information , 2010, Int. J. Medical Informatics.
[9] Walt Detmar Meurers,et al. Readability assessment for text simplification: From analysing documents to identifying sentential simplifications , 2014 .
[10] Alastair K Denniston,et al. Readability assessment of online ophthalmic patient information. , 2013, JAMA ophthalmology.
[11] Danielle S. McNamara,et al. Text readability and intuitive simplification: A comparison of readability formulas , 2011 .
[12] J. Whelan,et al. A Text Comprehension Approach to Questionnaire Readability: An Example Using Gambling Disorder Measures , 2018, Psychological assessment.
[13] Olga Cherednichenko,et al. Complex Term Identification for Ukrainian Medical Texts , 2018, IDDM.
[14] Xiaojun Wan,et al. Automatic Text Simplification , 2018, Computational Linguistics.
[15] Maria Kvist,et al. Medical text simplification using synonym replacement: Adapting assessment of word difficulty to a compounding language , 2014, PITR@EACL.