The effects of COVID-19 lockdown on glycaemic control and lipid profile in patients with type 2 diabetes: a systematic review and meta-analysis
The impact of the COVID-19 lockdown on glycaemic control and other metabolic parameters
in patients with type 2 diabetes is still evolving. Aim: This systematic review and meta …
in patients with type 2 diabetes is still evolving. Aim: This systematic review and meta …
Increased risk of COVID-19 in patients with diabetes mellitus—Current challenges in pathophysiology, treatment and prevention
T Gęca, K Wojtowicz, P Guzik, T Gora - International journal of …, 2022 - mdpi.com
Coronavirus disease—COVID-19 (coronavirus disease 2019) has become the cause of the
global pandemic in the last three years. Its etiological factor is SARS-CoV-2 (Severe Acute …
global pandemic in the last three years. Its etiological factor is SARS-CoV-2 (Severe Acute …
Eight pruning deep learning models for low storage and high-speed COVID-19 computed tomography lung segmentation and heatmap-based lesion localization: A …
Abstract Background COVLIAS 1.0: an automated lung segmentation was designed for
COVID-19 diagnosis. It has issues related to storage space and speed. This study shows …
COVID-19 diagnosis. It has issues related to storage space and speed. This study shows …
Economics of artificial intelligence in healthcare: diagnosis vs. treatment
NN Khanna, MA Maindarkar, V Viswanathan… - Healthcare, 2022 - mdpi.com
Motivation: The price of medical treatment continues to rise due to (i) an increasing
population;(ii) an aging human growth;(iii) disease prevalence;(iv) a rise in the frequency of …
population;(ii) an aging human growth;(iii) disease prevalence;(iv) a rise in the frequency of …
Understanding the bias in machine learning systems for cardiovascular disease risk assessment: The first of its kind review
Abstract Background Artificial Intelligence (AI), in particular, machine learning (ML) has
shown promising results in coronary artery disease (CAD) or cardiovascular disease (CVD) …
shown promising results in coronary artery disease (CAD) or cardiovascular disease (CVD) …
Deep learning artificial intelligence framework for multiclass coronary artery disease prediction using combination of conventional risk factors, carotid ultrasound, and …
Objective Cardiovascular disease (CVD) is a major healthcare challenge and therefore early
risk assessment is vital. Previous assessment techniques use either “conventional CVD risk …
risk assessment is vital. Previous assessment techniques use either “conventional CVD risk …
Attention-based UNet deep learning model for plaque segmentation in carotid ultrasound for stroke risk stratification: an artificial intelligence paradigm
Stroke and cardiovascular diseases (CVD) significantly affect the world population. The
early detection of such events may prevent the burden of death and costly surgery …
early detection of such events may prevent the burden of death and costly surgery …
Five strategies for bias estimation in artificial intelligence-based hybrid deep learning for acute respiratory distress syndrome COVID-19 lung infected patients using …
Coronavirus 2019 (COVID-19) has led to a global pandemic infecting 224 million people
and has caused 4.6 million deaths. Nearly 80 Artificial Intelligence (AI) articles have been …
and has caused 4.6 million deaths. Nearly 80 Artificial Intelligence (AI) articles have been …
COVLIAS 2.0-cXAI: Cloud-based explainable deep learning system for COVID-19 lesion localization in computed tomography scans
Background: The previous COVID-19 lung diagnosis system lacks both scientific validation
and the role of explainable artificial intelligence (AI) for understanding lesion localization …
and the role of explainable artificial intelligence (AI) for understanding lesion localization …
COVLIAS 1.0: lung segmentation in COVID-19 computed tomography scans using hybrid deep learning artificial intelligence models
Background: COVID-19 lung segmentation using Computed Tomography (CT) scans is
important for the diagnosis of lung severity. The process of automated lung segmentation is …
important for the diagnosis of lung severity. The process of automated lung segmentation is …