@inproceedings{5cdd4fe7820e4d15807b03d75cb47414,
title = "Identifying recent telemedicine research trends using a natural language processing approach",
abstract = "Conventional literature review processes undertaken by hum an experts require considerable effort. Automating them is elusive due to subtlety of concepts and complexity of interrelationships implicit In text semantics, However, when assessing topics relating to current trends, these factors are less important as there is inherent breadth and diversity in the text which countermands the need for expertise. This paper presents an approach for trend topic analysis using simple bibliometrics of Term Frequency and Keyword Selection, extracted with natural language processing tools NL.TK and AntConc. This approach is applied to a case study of identifying trends in Telemedicine research in South Africa based on 2019 pubflearlens included in PubMed. Lists of topics generated by the analysis methods show consistency in identified trends and suggest their suitability to categorise small focussed corpora.",
keywords = "Bibliometrics, Literature review, Naturallanguage processing, Telemedicine",
author = "Anthony Maeder and Martyn George and Bertha Naveda",
year = "2020",
month = sep,
doi = "10.1109/icABCD49160.2020.9183816",
language = "English",
series = "2020 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2020 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Sameerchand Pudaruth and Upasana Singh",
booktitle = "2020 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2020 - Proceedings",
note = "2020 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2020 ; Conference date: 06-08-2020 Through 07-08-2020",
}