Machine learning and decision support in critical care

AEW Johnson, MM Ghassemi, S Nemati… - Proceedings of the …, 2016 - ieeexplore.ieee.org
Clinical data management systems typically provide caregiver teams with useful information,
derived from large, sometimes highly heterogeneous, data sources that are often changing …

Systematic review of current natural language processing methods and applications in cardiology

MR Turchioe, A Volodarskiy, J Pathak, DN Wright… - Heart, 2022 - heart.bmj.com
Natural language processing (NLP) is a set of automated methods to organise and evaluate
the information contained in unstructured clinical notes, which are a rich source of real-world …

Artificial intelligence in nursing: Priorities and opportunities from an international invitational think‐tank of the Nursing and Artificial Intelligence Leadership …

CE Ronquillo, LM Peltonen, L Pruinelli… - Journal of advanced …, 2021 - Wiley Online Library
Aim To develop a consensus paper on the central points of an international invitational think‐
tank on nursing and artificial intelligence (AI). Methods We established the Nursing and …

Biases in electronic health record data due to processes within the healthcare system: retrospective observational study

D Agniel, IS Kohane, GM Weber - Bmj, 2018 - bmj.com
Objective To evaluate on a large scale, across 272 common types of laboratory tests, the
impact of healthcare processes on the predictive value of electronic health record (EHR) …

Quality of nursing documentation: Paper‐based health records versus electronic‐based health records

L Akhu‐Zaheya, R Al‐Maaitah… - Journal of clinical …, 2018 - Wiley Online Library
Aims and objectives To assess and compare the quality of paper‐based and electronic‐
based health records. The comparison examined three criteria: content, documentation …

Physician understanding, explainability, and trust in a hypothetical machine learning risk calculator

WK Diprose, N Buist, N Hua, Q Thurier… - Journal of the …, 2020 - academic.oup.com
Objective Implementation of machine learning (ML) may be limited by patients' right to
“meaningful information about the logic involved” when ML influences healthcare decisions …

“Big data” and the electronic health record

MK Ross, W Wei… - Yearbook of medical …, 2014 - thieme-connect.com
Objectives: Implementation of Electronic Health Record (EHR) systems continues to expand.
The massive number of patient encounters results in high amounts of stored data …

[HTML][HTML] Nursing documentation practice and associated factors among nurses in public hospitals, Tigray, Ethiopia

H Tasew, T Mariye, G Teklay - BMC research notes, 2019 - Springer
Objective The objective of this study was to investigate documentation practice and factors
affecting documentation practice among nurses working in public hospital of Tigray region …

The role of electronic medical records in improving the quality of health care services: Comparative study

O Ayaad, A Alloubani, EA ALhajaa, M Farhan… - International journal of …, 2019 - Elsevier
Purpose The purpose of this study is to identify the quality of health care services'
differences between adopted Electronic Medical Record (EMR) and paper-based record …

[HTML][HTML] Development and validation of early warning score system: A systematic literature review

LH Fu, J Schwartz, A Moy, C Knaplund, MJ Kang… - Journal of biomedical …, 2020 - Elsevier
Objectives This review aims to: 1) evaluate the quality of model reporting, 2) provide an
overview of methodology for developing and validating Early Warning Score Systems …