Applications of microwaves in medicine leveraging artificial intelligence: Future perspectives

K Gopalakrishnan, A Adhikari, N Pallipamu, M Singh… - Electronics, 2023 - mdpi.com
Microwaves are non-ionizing electromagnetic radiation with waves of electrical and
magnetic energy transmitted at different frequencies. They are widely used in various …

ECMO PAL: using deep neural networks for survival prediction in venoarterial extracorporeal membrane oxygenation

AF Stephens, M Šeman, A Diehl, D Pilcher… - Intensive Care …, 2023 - Springer
Purpose Venoarterial extracorporeal membrane oxygenation (VA-ECMO) is a complex and
high-risk life support modality used in severe cardiorespiratory failure. ECMO survival scores …

Predicting Cardiopulmonary Arrest with Digital Biomarkers: A Systematic Review

GD De Sario Velasquez, AJ Forte, CJ McLeod… - Journal of Clinical …, 2023 - mdpi.com
(1) Background: Telemetry units allow the continuous monitoring of vital signs and ECG of
patients. Such physiological indicators work as the digital signatures and biomarkers of …

[HTML][HTML] Human and AI: Collaborative Medicine in the Age of Technology

M Farrokhi, F Taheri, M Farrokhi, N Emtiazi, M Talebi… - Kindle, 2024 - preferpub.org
In the era of rapidly advancing technology, the collaboration between humans and artificial
intelligence (AI) is reshaping the landscape of medicine, ushering in an era of collaborative …

Intelligent clinical decision support

MR Pinsky, A Dubrawski, G Clermont - Sensors, 2022 - mdpi.com
Early recognition of pathologic cardiorespiratory stress and forecasting cardiorespiratory
decompensation in the critically ill is difficult even in highly monitored patients in the …

Quantifying deep neural network uncertainty for atrial fibrillation detection with limited labels

B Chen, G Javadi, A Hamilton, S Sibley, P Laird… - Scientific Reports, 2022 - nature.com
Atrial fibrillation (AF) is the most common arrhythmia found in the intensive care unit (ICU),
and is associated with many adverse outcomes. Effective handling of AF and similar …

Leveraging data science and novel technologies to develop and implement precision medicine strategies in critical care

LN Sanchez-Pinto, SV Bhavani… - Critical Care …, 2023 - criticalcare.theclinics.com
Heterogeneity is a pervasive feature of critical illness syndromes. Patients in the intensive
care unit (ICU) are injured or develop critical illness for a plethora of reasons. On any given …

Optimized arterial line artifact identification algorithm cleans high-frequency arterial line data with high accuracy in critically ill patients

JM Khan, DM Maslove, JG Boyd - Critical Care Explorations, 2022 - journals.lww.com
OBJECTIVES: High-frequency data streams of vital signs may be used to generate
individualized hemodynamic targets for critically ill patients. Central to this precision …

Robust Machine Learning in Critical Care—Software Engineering and Medical Perspectives

M Staron, HO Herges, S Naredi, L Block… - 2021 IEEE/ACM 1st …, 2021 - ieeexplore.ieee.org
Using machine learning in clinical practice poses hard requirements on explainability,
reliability, replicability and robustness of these systems. Therefore, developing reliable …

Novel approaches to capturing and using continuous cardiorespiratory physiological data in hospitalized children

SB Walker, CM Badke, MS Carroll, KS Honegger… - Pediatric …, 2023 - nature.com
Continuous cardiorespiratory physiological monitoring is a cornerstone of care in
hospitalized children. The data generated by monitoring devices coupled with machine …