id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_s6yodfvne5aitj5qu4pbwdf2du	Elizabeth Toon	Text-Mining and the History of Medicine: Big Data, Big Questions?	2016	3	.pdf	application/pdf	2059	227	24	Text-Mining and the History of Medicine: Big Data, Big Questions? motivated our involvement in a collaborative project using text mining tools with medical National Centre for Text Mining (NaCTeM) to work on a project funded by the UK Arts name suggests, NaCTeM2 develops text mining tools, mostly for academic use.3 Our team to explore how such a search could provide new ways of working with series of medical Text mining (TM) uses digital tools to detect the structure of textual information, then data as representing entities of different types, such as place names, medical conditions, customised approach to correcting OCR errors in medical historical texts,8 which means We then worked with NaCTeM colleagues to analyse sample text, identifying entities medical texts proved much more difficult than teaching it to identify simpler entities like Ananiadou, 'Customised OCR Correction for Historical Medical Text', https://www.cambridge.org/core/terms https://www.cambridge.org/core/terms https://www.cambridge.org/core/terms https://www.cambridge.org/core/terms https://www.cambridge.org/core/terms https://www.cambridge.org/core/terms	./cache/work_s6yodfvne5aitj5qu4pbwdf2du.pdf	./txt/work_s6yodfvne5aitj5qu4pbwdf2du.txt