Explainable artificial intelligence methods in combating pandemics: A systematic review
Despite the myriad peer-reviewed papers demonstrating novel Artificial Intelligence (AI)-
based solutions to COVID-19 challenges during the pandemic, few have made a significant …
based solutions to COVID-19 challenges during the pandemic, few have made a significant …
Management of COVID-19-associated acute respiratory failure with alternatives to invasive mechanical ventilation: high-flow oxygen, continuous positive airway …
B Bonnesen, JUS Jensen, KN Jeschke… - Diagnostics, 2021 - mdpi.com
Patients admitted to hospital with coronavirus disease 2019 (COVID-19) may develop acute
respiratory failure (ARF) with compromised gas exchange. These patients require oxygen …
respiratory failure (ARF) with compromised gas exchange. These patients require oxygen …
FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare
Despite major advances in artificial intelligence (AI) for medicine and healthcare, the
deployment and adoption of AI technologies remain limited in real-world clinical practice. In …
deployment and adoption of AI technologies remain limited in real-world clinical practice. In …
Pharmacophenotype identification of intensive care unit medications using unsupervised cluster analysis of the ICURx common data model
Background Identifying patterns within ICU medication regimens may help artificial
intelligence algorithms to better predict patient outcomes; however, machine learning …
intelligence algorithms to better predict patient outcomes; however, machine learning …
[HTML][HTML] Multitask learning with recurrent neural networks for acute respiratory distress syndrome prediction using only electronic health record data: model …
Background Acute respiratory distress syndrome (ARDS) is a condition that is often
considered to have broad and subjective diagnostic criteria and is associated with …
considered to have broad and subjective diagnostic criteria and is associated with …
Cluster analysis driven by unsupervised latent feature learning of medications to identify novel pharmacophenotypes of critically ill patients
Unsupervised clustering of intensive care unit (ICU) medications may identify unique
medication clusters (ie, pharmacophenotypes) in critically ill adults. We performed an …
medication clusters (ie, pharmacophenotypes) in critically ill adults. We performed an …
A machine learning model on Real World Data for predicting progression to Acute Respiratory Distress Syndrome (ARDS) among COVID-19 patients
N Lazzarini, A Filippoupolitis, P Manzione… - PLoS …, 2022 - journals.plos.org
Introduction Identifying COVID-19 patients that are most likely to progress to a severe
infection is crucial for optimizing care management and increasing the likelihood of survival …
infection is crucial for optimizing care management and increasing the likelihood of survival …
Artificial intelligence–aided diagnosis model for acute respiratory distress syndrome combining clinical data and chest radiographs
Objective The aim of this study was to develop an artificial intelligence–based model to
detect the presence of acute respiratory distress syndrome (ARDS) using clinical data and …
detect the presence of acute respiratory distress syndrome (ARDS) using clinical data and …
Developing and evaluating a machine-learning-based algorithm to predict the incidence and severity of ARDS with continuous non-invasive parameters from ordinary …
W Wu, Y Wang, J Tang, M Yu, J Yuan… - Computer Methods and …, 2023 - Elsevier
Objectives Major observational studies report that the mortality rate of acute respiratory
distress syndrome (ARDS) is close to 40%. Different treatment strategies are required for …
distress syndrome (ARDS) is close to 40%. Different treatment strategies are required for …
Machine learning approaches to identify discriminative signatures of volatile organic compounds (VOCs) from bacteria and fungi using SPME-DART-MS
M Arora, SC Zambrzycki, JM Levy, A Esper, JK Frediani… - Metabolites, 2022 - mdpi.com
Point-of-care screening tools are essential to expedite patient care and decrease reliance
on slow diagnostic tools (eg, microbial cultures) to identify pathogens and their associated …
on slow diagnostic tools (eg, microbial cultures) to identify pathogens and their associated …