Towards Automated Screening of Literature on Artificial Intelligence in Nursing
Björne Jari; Sequeira Lydia; Jeon Eunjoo; Veeranki Sai Pavan Kumar; Celin Sven; Topaz Maxim; Tayaben Jude; Block Lori; Ronquillo Charlene Esteban; Peltonen Laura-Maria; Kreiner Karl; Mitchell James; Alhuwail Dari; Ožegović Gabriela; Moen Hans
Towards Automated Screening of Literature on Artificial Intelligence in Nursing
Björne Jari
Sequeira Lydia
Jeon Eunjoo
Veeranki Sai Pavan Kumar
Celin Sven
Topaz Maxim
Tayaben Jude
Block Lori
Ronquillo Charlene Esteban
Peltonen Laura-Maria
Kreiner Karl
Mitchell James
Alhuwail Dari
Ožegović Gabriela
Moen Hans
Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe2022091258735
https://urn.fi/URN:NBN:fi-fe2022091258735
Tiivistelmä
We evaluate the performance of multiple text classification methods used to automate the screening of article abstracts in terms of their relevance to a topic of interest. The aim is to develop a system that can be first trained on a set of manually screened article abstracts before using it to identify additional articles on the same topic. Here the focus is on articles related to the topic "artificial intelligence in nursing". Eight text classification methods are tested, as well as two simple ensemble systems. The results indicate that it is feasible to use text classification technology to support the manual screening process of article abstracts when conducting a literature review. The best results are achieved by an ensemble system, which achieves a F1-score of 0.41, with a sensitivity of 0.54 and a specificity of 0.96. Future work directions are discussed.
Kokoelmat
- Rinnakkaistallenteet [19206]