Towards Automated Screening of Literature on Artificial Intelligence in Nursing

Hans Moen; Dari Alhuwail; Jari Björne; Lori Block; Sven Celin; Eunjoo Jeon; Karl Kreiner; James Mitchell; Gabriela Ozegović; Charlene Esteban Ronquillo; Lydia Sequeira; Jude Tayaben; Maxim Topaz; Sai Pavan Kumar Veeranki; Laura Maria Peltonen

doi:10.3233/SHTI220155

Towards Automated Screening of Literature on Artificial Intelligence in Nursing

Hans Moen^*
, Dari Alhuwail
, Jari Björne
, Lori Block
, Sven Celin
, Eunjoo Jeon
, Karl Kreiner
, James Mitchell
, Gabriela Ozegović
, Charlene Esteban Ronquillo
, Lydia Sequeira
, Jude Tayaben
, Maxim Topaz
, Sai Pavan Kumar Veeranki
, Laura Maria Peltonen

^*Corresponding author for this work

Not published at Aalto University

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

5 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	MEDINFO 2021
Subtitle of host publication	One World, One Health - Global Partnership for Digital Innovation - Proceedings of the 18th World Congress on Medical and Health Informatics
Editors	Paula Otero, Philip Scott, Susan Z. Martin, Elaine Huesing
Publisher	IOS Press
Pages	637-640
Number of pages	4
ISBN (Electronic)	978-1-64368-264-8
DOIs	https://doi.org/10.3233/SHTI220155
Publication status	Published - 6 Jun 2022
MoE publication type	A4 Conference publication
Event	World Congress on Medical and Health Informatics - Virtual, Online Duration: 2 Oct 2021 → 4 Oct 2021 Conference number: 18

Publication series

Name	Studies in Health Technology and Informatics
Publisher	IOS Press
Volume	290
ISSN (Print)	0926-9630
ISSN (Electronic)	1879-8365

Conference

Conference	World Congress on Medical and Health Informatics
Abbreviated title	MEDINFO
City	Virtual, Online
Period	02/10/2021 → 04/10/2021

Funding

This paper was initiated and written by the members of the Students and Emerging Professionals Special Interest Group of the International Medical Informatics Association. The research was supported by the Academy of Finland (315376).

Keywords

Natural Language Processing
Nursing
Review

Access to Document

10.3233/SHTI220155

Cite this

Moen, H., Alhuwail, D., Björne, J., Block, L., Celin, S., Jeon, E., Kreiner, K., Mitchell, J., Ozegović, G., Ronquillo, C. E., Sequeira, L., Tayaben, J., Topaz, M., Veeranki, S. P. K., & Peltonen, L. M. (2022). Towards Automated Screening of Literature on Artificial Intelligence in Nursing. In P. Otero, P. Scott, S. Z. Martin, & E. Huesing (Eds.), MEDINFO 2021: One World, One Health - Global Partnership for Digital Innovation - Proceedings of the 18th World Congress on Medical and Health Informatics (pp. 637-640). (Studies in Health Technology and Informatics; Vol. 290). IOS Press. https://doi.org/10.3233/SHTI220155

Moen, Hans ; Alhuwail, Dari ; Björne, Jari et al. / Towards Automated Screening of Literature on Artificial Intelligence in Nursing. MEDINFO 2021: One World, One Health - Global Partnership for Digital Innovation - Proceedings of the 18th World Congress on Medical and Health Informatics. editor / Paula Otero ; Philip Scott ; Susan Z. Martin ; Elaine Huesing. IOS Press, 2022. pp. 637-640 (Studies in Health Technology and Informatics).

@inproceedings{a7047ff0e3ef423096d8331a8d367210,

title = "Towards Automated Screening of Literature on Artificial Intelligence in Nursing",

abstract = "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.",

keywords = "Natural Language Processing, Nursing, Review",

author = "Hans Moen and Dari Alhuwail and Jari Bj{\"o}rne and Lori Block and Sven Celin and Eunjoo Jeon and Karl Kreiner and James Mitchell and Gabriela Ozegovi{\'c} and Ronquillo, \{Charlene Esteban\} and Lydia Sequeira and Jude Tayaben and Maxim Topaz and Veeranki, \{Sai Pavan Kumar\} and Peltonen, \{Laura Maria\}",

note = "Funding Information: This paper was initiated and written by the members of the Students and Emerging Professionals Special Interest Group of the International Medical Informatics Association. The research was supported by the Academy of Finland (315376). Publisher Copyright: {\textcopyright} 2022 International Medical Informatics Association (IMIA) and IOS Press.; World Congress on Medical and Health Informatics, MEDINFO ; Conference date: 02-10-2021 Through 04-10-2021",

year = "2022",

month = jun,

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doi = "10.3233/SHTI220155",

language = "English",

series = "Studies in Health Technology and Informatics",

publisher = "IOS Press",

pages = "637--640",

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Moen, H, Alhuwail, D, Björne, J, Block, L, Celin, S, Jeon, E, Kreiner, K, Mitchell, J, Ozegović, G, Ronquillo, CE, Sequeira, L, Tayaben, J, Topaz, M, Veeranki, SPK & Peltonen, LM 2022, Towards Automated Screening of Literature on Artificial Intelligence in Nursing. in P Otero, P Scott, SZ Martin & E Huesing (eds), MEDINFO 2021: One World, One Health - Global Partnership for Digital Innovation - Proceedings of the 18th World Congress on Medical and Health Informatics. Studies in Health Technology and Informatics, vol. 290, IOS Press, pp. 637-640, World Congress on Medical and Health Informatics, Virtual, Online, 02/10/2021. https://doi.org/10.3233/SHTI220155

Towards Automated Screening of Literature on Artificial Intelligence in Nursing. / Moen, Hans; Alhuwail, Dari; Björne, Jari et al.
MEDINFO 2021: One World, One Health - Global Partnership for Digital Innovation - Proceedings of the 18th World Congress on Medical and Health Informatics. ed. / Paula Otero; Philip Scott; Susan Z. Martin; Elaine Huesing. IOS Press, 2022. p. 637-640 (Studies in Health Technology and Informatics; Vol. 290).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

T1 - Towards Automated Screening of Literature on Artificial Intelligence in Nursing

AU - Moen, Hans

AU - Alhuwail, Dari

AU - Björne, Jari

AU - Block, Lori

AU - Celin, Sven

AU - Jeon, Eunjoo

AU - Kreiner, Karl

AU - Mitchell, James

AU - Ozegović, Gabriela

AU - Ronquillo, Charlene Esteban

AU - Sequeira, Lydia

AU - Tayaben, Jude

AU - Topaz, Maxim

AU - Veeranki, Sai Pavan Kumar

AU - Peltonen, Laura Maria

N1 - Conference code: 18

PY - 2022/6/6

Y1 - 2022/6/6

N2 - 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.

AB - 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.

KW - Natural Language Processing

KW - Nursing

KW - Review

UR - https://www.scopus.com/pages/publications/85131483263

U2 - 10.3233/SHTI220155

DO - 10.3233/SHTI220155

M3 - Conference article in proceedings

C2 - 35673094

AN - SCOPUS:85131483263

T3 - Studies in Health Technology and Informatics

SP - 637

EP - 640

BT - MEDINFO 2021

A2 - Otero, Paula

A2 - Scott, Philip

A2 - Martin, Susan Z.

A2 - Huesing, Elaine

PB - IOS Press

T2 - World Congress on Medical and Health Informatics

Y2 - 2 October 2021 through 4 October 2021

ER -

Moen H, Alhuwail D, Björne J, Block L, Celin S, Jeon E et al. Towards Automated Screening of Literature on Artificial Intelligence in Nursing. In Otero P, Scott P, Martin SZ, Huesing E, editors, MEDINFO 2021: One World, One Health - Global Partnership for Digital Innovation - Proceedings of the 18th World Congress on Medical and Health Informatics. IOS Press. 2022. p. 637-640. (Studies in Health Technology and Informatics). doi: 10.3233/SHTI220155

Towards Automated Screening of Literature on Artificial Intelligence in Nursing

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