This paper is in the following e-collection/theme issue:

Decision Support for Health Professionals (1191) Epidemiology (160) Pressure Ulcers and Decubitus Wounds (25)

Published on in Vol 3, No 1 (2015): Jan-Mar

On-Admission Pressure Ulcer Prediction Using the Nursing Needs Score

On-Admission Pressure Ulcer Prediction Using the Nursing Needs Score

On-Admission Pressure Ulcer Prediction Using the Nursing Needs Score

Authors of this article:

Yoko Nakamura1 Author Orcid Image ;   A. Ammar Ghaibeh1 Author Orcid Image ;   Yoko Setoguchi1 Author Orcid Image ;   Kazue Mitani2 Author Orcid Image ;   Yoshiro Abe3 Author Orcid Image ;   Ichiro Hashimoto3 Author Orcid Image ;   Hiroki Moriguchi1 Author Orcid Image
Article Authors Cited by (8) Tweetations (1) Metrics

Journals

  1. Uemura H, Ghaibeh A, Katsuura-Kamano S, Yamaguchi M, Bahari T, Ishizu M, Moriguchi H, Arisawa K. Systemic inflammation and family history in relation to the prevalence of type 2 diabetes based on an alternating decision tree. Scientific Reports 2017;7(1) View
  2. Setoguchi Y, Ghaibeh A, Mitani K, Abe Y, Hashimoto I, Moriguchi H. Predictability of Pressure Ulcers Based on Operation Duration, Transfer Activity, and Body Mass Index Through the Use of an Alternating Decision Tree. The Journal of Medical Investigation 2016;63(3.4):248 View
  3. Han S, Kim Y, Hwang J, Lee J, Song M. Predictors of hospital‐acquired pressure ulcers among older adult inpatients. Journal of Clinical Nursing 2018;27(19-20):3780 View
  4. Raff L, Waller H, Griffin R, Kerby J, Bosarge P. Identification of Risk Factors for the Development of Pressure Ulcers Despite Standard Screening Methodology and Prophylaxis in Trauma Patients. Advances in Skin & Wound Care 2016;29(7):329 View
  5. Ladios-Martin M, Fernández-de-Maya J, Ballesta-López F, Belso-Garzas A, Mas-Asencio M, Cabañero-Martínez M. Predictive Modeling of Pressure Injury Risk in Patients Admitted to an Intensive Care Unit. American Journal of Critical Care 2020;29(4):e70 View
  6. Levy J, Lima J, Miller M, Freed G, O'Malley A, Emeny R. Machine Learning Approaches for Hospital Acquired Pressure Injuries: A Retrospective Study of Electronic Medical Records. Frontiers in Medical Technology 2022;4 View
  7. Ma Y, He X, Yang T, Yang Y, Yang Z, Gao T, Yan F, Yan B, Wang J, Han L. Evaluation of the risk prediction model of pressure injuries in hospitalized patient: A systematic review and meta‐analysis. Journal of Clinical Nursing 2024 View

Books/Policy Documents

  1. Kasem A, Ammar Ghaibeh A, Moriguchi H. Computational Intelligence in Information Systems. View