Challenges and prospects of visual contactless physiological monitoring in clinical study
The monitoring of physiological parameters is a crucial topic in promoting human health and
an indispensable approach for assessing physiological status and diagnosing diseases …
an indispensable approach for assessing physiological status and diagnosing diseases …
Prognostic models in COVID-19 infection that predict severity: a systematic review
Current evidence on COVID-19 prognostic models is inconsistent and clinical applicability
remains controversial. We performed a systematic review to summarize and critically …
remains controversial. We performed a systematic review to summarize and critically …
[PDF][PDF] Examination of the Effects of Long-term COVID-19 Impacts on Patients with Neurological Disabilities Using a Neuro machine Learning Model
A Vaniprabha, J Logeshwaran… - … Journal of Neurology …, 2022 - researchgate.net
Currently, studies have shown that one in three people infected with coronavirus disease-19
(COVID-19) is likely to have had long-term exposure to COVID-19, known as long-term …
(COVID-19) is likely to have had long-term exposure to COVID-19, known as long-term …
Using machine learning in prediction of ICU admission, mortality, and length of stay in the early stage of admission of COVID-19 patients
S Saadatmand, K Salimifard, R Mohammadi… - Annals of Operations …, 2023 - Springer
The recent COVID-19 pandemic has affected health systems across the world. Especially,
Intensive Care Units (ICUs) have played a pivotal role in the treatment of critically-ill patients …
Intensive Care Units (ICUs) have played a pivotal role in the treatment of critically-ill patients …
A comparative study of explainable ensemble learning and logistic regression for predicting in-hospital mortality in the emergency department
This study addresses the challenges associated with emergency department (ED)
overcrowding and emphasizes the need for efficient risk stratification tools to identify high …
overcrowding and emphasizes the need for efficient risk stratification tools to identify high …
The economics of deep and machine learning-based algorithms for COVID-19 prediction, detection, and diagnosis shaping the organizational management of …
G Lăzăroiu, T Gedeon, E Rogalska… - Oeconomia …, 2024 - cejsh.icm.edu.pl
Research background: Deep and machine learning-based algorithms can assist in COVID-
19 image-based medical diagnosis and symptom tracing, optimize intensive care unit …
19 image-based medical diagnosis and symptom tracing, optimize intensive care unit …
Comparing machine learning algorithms to predict COVID‑19 mortality using a dataset including chest computed tomography severity score data
SS Zakariaee, N Naderi, M Ebrahimi… - Scientific reports, 2023 - nature.com
Since the beginning of the COVID-19 pandemic, new and non-invasive digital technologies
such as artificial intelligence (AI) had been introduced for mortality prediction of COVID-19 …
such as artificial intelligence (AI) had been introduced for mortality prediction of COVID-19 …
Generalizable machine learning approach for COVID-19 mortality risk prediction using on-admission clinical and laboratory features
We aimed to propose a mortality risk prediction model using on-admission clinical and
laboratory predictors. We used a dataset of confirmed COVID-19 patients admitted to three …
laboratory predictors. We used a dataset of confirmed COVID-19 patients admitted to three …
Machine learning algorithms in sepsis
Sepsis remains a significant global health challenge due to its high mortality and morbidity,
compounded by the difficulty of early detection given its variable clinical manifestations. The …
compounded by the difficulty of early detection given its variable clinical manifestations. The …
[HTML][HTML] Predicting hospital readmission risk in patients with COVID-19: A machine learning approach
MR Afrash, H Kazemi-Arpanahi… - Informatics in medicine …, 2022 - Elsevier
Abstract Introduction The Coronavirus 2019 (COVID-19) epidemic stunned the health
systems with severe scarcities in hospital resources. In this critical situation, decreasing …
systems with severe scarcities in hospital resources. In this critical situation, decreasing …