[HTML][HTML] Application scenarios for artificial intelligence in nursing care: rapid review

K Seibert, D Domhoff, D Bruch, M Schulte-Althoff… - Journal of medical …, 2021 - jmir.org
Background Artificial intelligence (AI) holds the promise of supporting nurses' clinical
decision-making in complex care situations or conducting tasks that are remote from direct …

Machine Learning and the Future of Cardiovascular Care: JACC State-of-the-Art Review

G Quer, R Arnaout, M Henne, R Arnaout - Journal of the American College …, 2021 - jacc.org
The role of physicians has always been to synthesize the data available to them to identify
diagnostic patterns that guide treatment and follow response. Today, increasingly …

Outlook of pandemic preparedness in a post-COVID-19 world

BA Williams, CH Jones, V Welch, JM True - npj Vaccines, 2023 - nature.com
The COVID-19 pandemic was met with rapid, unprecedented global collaboration and
action. Even still, the public health, societal, and economic impact may be felt for years to …

Use of Artificial Intelligence in Improving Outcomes in Heart Disease: A Scientific Statement From the American Heart Association

AA Armoundas, SM Narayan, DK Arnett… - Circulation, 2024 - Am Heart Assoc
A major focus of academia, industry, and global governmental agencies is to develop and
apply artificial intelligence and other advanced analytical tools to transform health care …

Computational approaches to alleviate alarm fatigue in intensive care medicine: A systematic literature review

J Chromik, SAI Klopfenstein, B Pfitzner… - Frontiers in digital …, 2022 - frontiersin.org
Patient monitoring technology has been used to guide therapy and alert staff when a vital
sign leaves a predefined range in the intensive care unit (ICU) for decades. However, large …

Clinical significance, challenges and limitations in using artificial intelligence for electrocardiography-based diagnosis

CT Chung, S Lee, E King, T Liu, AA Armoundas… - International journal of …, 2022 - Springer
Cardiovascular diseases are one of the leading global causes of mortality. Currently,
clinicians rely on their own analyses or automated analyses of the electrocardiogram (ECG) …

Technology-enabled hospital at home: innovation for acute care at home

J Conley, GD Snyder, D Whitehead… - … Catalyst Innovations in …, 2022 - catalyst.nejm.org
Since 2016, two hospital at home programs at Mass General Brigham have cared for more
than 2,000 patients and have developed significant experience leveraging technology to …

[HTML][HTML] A standardized clinical data harmonization pipeline for scalable ai application deployment (fhir-dhp): Validation and usability study

E Williams, M Kienast, E Medawar… - JMIR Medical …, 2023 - medinform.jmir.org
Background Increasing digitalization in the medical domain gives rise to large amounts of
health care data, which has the potential to expand clinical knowledge and transform patient …

A contrastive learning approach for ICU false arrhythmia alarm reduction

Y Zhou, G Zhao, J Li, G Sun, X Qian, B Moody… - Scientific reports, 2022 - nature.com
The high rate of false arrhythmia alarms in Intensive Care Units (ICUs) can lead to disruption
of care, negatively impacting patients' health through noise disturbances, and slow staff …

Real‐time arrhythmia detection using hybrid convolutional neural networks

SC Bollepalli, RK Sevakula… - Journal of the …, 2021 - Am Heart Assoc
Background Accurate detection of arrhythmic events in the intensive care units (ICU) is of
paramount significance in providing timely care. However, traditional ICU monitors generate …