Task-technology fit model: Modelling and assessing the nurses’ satisfaction with health information system using AI prediction models

field_of_study

Blank

university

Al-Quds Open University

authors

Alhendawi K.M.

authors_full_names

Alhendawi, Kamal Mohammed (55654514100)

authors_id

55654514100

year

2024

source_title

International Journal of Healthcare Management

article_title

Task-technology fit model: Modelling and assessing the nurses’ satisfaction with health information system using AI prediction models

volume

17

issue

1

page_start

12

page_end

24

publisher

Taylor and Francis Ltd.

affiliations

Al-Quds Open University, Gaza, Palestine

authors_with_affiliations

Alhendawi K.M., Al-Quds Open University, Gaza, Palestine

corresponding_author

K.M. Alhendawi; Al-Quds Open University, Gaza, 0097, Palestine; email: Hindawi.kamal@yahoo.com

cited_by

9

doi

10.1080/20479700.2022.2136881

author_keywords

artificial intelligence (AI); Artificial neural network (ANN); health information system (HIS); prediction model; Rapidminer

index_keywords

article; artificial intelligence; artificial neural network; human; human experiment; manager; medical information system; nurse; performance indicator; prediction; questionnaire; recall; regression model; satisfaction