scholarly article | Q13442814 |
P50 | author | Dheeraj Raju | Q59194211 |
P2093 | author name string | Patricia A Patrician | |
Xiaogang Su | |||
Lori A Loan | |||
Mary S McCarthy | |||
P433 | issue | 1 | |
P407 | language of work or name | English | Q1860 |
P921 | main subject | data mining | Q172491 |
P304 | page(s) | 102-111 | |
P577 | publication date | 2014-08-18 | |
P1433 | published in | International Journal of Nursing Studies | Q15753849 |
P1476 | title | Exploring factors associated with pressure ulcers: a data mining approach | |
P478 | volume | 52 |
Q55431478 | A Systematic Review on Healthcare Analytics: Application and Theoretical Perspective of Data Mining. |
Q37677676 | Applying of Decision Tree Analysis to Risk Factors Associated with Pressure Ulcers in Long-Term Care Facilities |
Q90607264 | Big data analytics for preventive medicine |
Q50338079 | Comparison of Models for the Prediction of Medical Costs of Spinal Fusion in Taiwan Diagnosis-Related Groups by Machine Learning Algorithms |
Q53792386 | Educational campaign to increase knowledge of pressure ulcers. |
Q38653235 | Harnessing electronic healthcare data for wound care research: Wound registry analytic guidelines for less-biased analyses |
Q46313586 | Hospital-Acquired Pressure Injury: Risk-Adjusted Comparisons in an Integrated Healthcare Delivery System |
Q38388401 | Predicting Functional Decline and Recovery for Residents in Veterans Affairs Nursing Homes |
Q58618754 | Predicting Pressure Injury in Critical Care Patients: A Machine-Learning Model |
Q60921716 | Prediction of postoperative complications of pediatric cataract patients using data mining |
Q92878465 | Predictive efficacy of the Braden Q Scale for pediatric pressure ulcer risk assessment in the PICU: a meta-analysis |
Q57178763 | Risk Adjustment for Hospital Characteristics Reduces Unexplained Hospital Variation in Pressure Injury Risk |
Q39670631 | Supplementing the Braden scale for pressure ulcer risk among medical inpatients: the contribution of self-reported symptoms and standard laboratory tests. |
Q92916981 | Using machine-learning methods to support health-care professionals in making admission decisions |