The clinical information systems response to the COVID-19 pandemic

JJ Reeves, NM Pageler, EC Wick… - Yearbook of medical …, 2021 - thieme-connect.com
Objective: The year 2020 was predominated by the coronavirus disease 2019 (COVID-19)
pandemic. The objective of this article is to review the areas in which clinical information …

Machine learning and artificial intelligence in neurosurgery: status, prospects, and challenges

TF Dagi, FG Barker, J Glass - Neurosurgery, 2021 - journals.lww.com
The purpose of this article is to introduce artificial intelligence (AI), machine learning (ML),
and related technologies to neurosurgeons, to review their current status, and to comment …

Tasks as needs: reframing the paradigm of clinical natural language processing research for real-world decision support

A Lederman, R Lederman… - Journal of the American …, 2022 - academic.oup.com
Electronic medical records are increasingly used to store patient information in hospitals and
other clinical settings. There has been a corresponding proliferation of clinical natural …

[HTML][HTML] Acceptance, barriers, and facilitators to implementing artificial intelligence–based decision support systems in emergency departments: quantitative and …

R Fujimori, K Liu, S Soeno, H Naraba… - JMIR formative …, 2022 - formative.jmir.org
Background: Despite the increasing availability of clinical decision support systems (CDSSs)
and rising expectation for CDSSs based on artificial intelligence (AI), little is known about the …

Investigation of the performance of machine learning classifiers for pneumonia detection in chest X-ray images

RE Al Mamlook, S Chen, HF Bzizi - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
Pneumonia is one of the serious and life-threatening diseases that is caused by a bacterial
or viral infection of the lungs and have the potential to result in severe consequences within …

The constrained-disorder principle assists in overcoming significant challenges in digital health: moving from “nice to have” to mandatory systems

N Hurvitz, Y Ilan - Clinics and Practice, 2023 - mdpi.com
The success of artificial intelligence depends on whether it can penetrate the boundaries of
evidence-based medicine, the lack of policies, and the resistance of medical professionals …

Prediction of acute hypertensive episodes in critically ill patients

N Itzhak, IM Pessach, R Moskovitch - Artificial intelligence in medicine, 2023 - Elsevier
Prevention and treatment of complications are the backbone of medical care, particularly in
critical care settings. Early detection and prompt intervention can potentially prevent …

[HTML][HTML] Assessing the economic value of clinical artificial intelligence: challenges and opportunities

N Hendrix, DL Veenstra, M Cheng, NC Anderson… - Value in Health, 2022 - Elsevier
Objectives Clinical artificial intelligence (AI) is a novel technology, and few economic
evaluations have focused on it to date. Before its wider implementation, it is important to …

Mining electronic health records using artificial intelligence: Bibliometric and content analyses for current research status and product conversion

J Liang, Y He, J Xie, X Fan, Y Liu, Q Wen… - Journal of Biomedical …, 2023 - Elsevier
Abstract Background The use of Electronic Health Records is the most important milestone
in the digitization and intelligence of the entire medical industry. AI can effectively mine the …

Examination and diagnosis of electronic patient records and their associated ethics: a scoping literature review

T Jacquemard, CP Doherty, MB Fitzsimons - BMC medical ethics, 2020 - Springer
Background Electronic patient record (EPR) technology is a key enabler for improvements to
healthcare service and management. To ensure these improvements and the means to …