Graph neural networks: foundation, frontiers and applications
The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …
recent years. Graph neural networks, also known as deep learning on graphs, graph …
[HTML][HTML] Artificial intelligence for COVID-19: Battling the pandemic with computational intelligence
The new coronavirus disease 2019 (COVID-19) has become a global pandemic leading to
over 180 million confirmed cases and nearly 4 million deaths until June 2021, according to …
over 180 million confirmed cases and nearly 4 million deaths until June 2021, according to …
Clinical sepsis phenotypes in critically ill patients
G Papathanakos, I Andrianopoulos, M Xenikakis… - Microorganisms, 2023 - mdpi.com
Sepsis, defined as the life-threatening dysregulated host response to an infection leading to
organ dysfunction, is considered as one of the leading causes of mortality worldwide …
organ dysfunction, is considered as one of the leading causes of mortality worldwide …
[HTML][HTML] An interpretable machine learning prognostic system for risk stratification in oropharyngeal cancer
Background The optimal management of oropharyngeal squamous cell carcinoma (OPSCC)
includes both surgical and non-surgical, that is,(chemo) radiotherapy treatment options and …
includes both surgical and non-surgical, that is,(chemo) radiotherapy treatment options and …
Identification of Parkinson's disease PACE subtypes and repurposing treatments through integrative analyses of multimodal data
Parkinson's disease (PD) is a serious neurodegenerative disorder marked by significant
clinical and progression heterogeneity. This study aimed at addressing heterogeneity of PD …
clinical and progression heterogeneity. This study aimed at addressing heterogeneity of PD …
Identification of robust protein associations with COVID-19 disease based on five clinical studies
Multiple studies have investigated the role of blood circulating proteins in COVID-19 disease
using the Olink affinity proteomics platform. However, study inclusion criteria and sample …
using the Olink affinity proteomics platform. However, study inclusion criteria and sample …
A multi-task Gaussian process self-attention neural network for real-time prediction of the need for mechanical ventilators in COVID-19 patients
Abstract Objective The Coronavirus Disease 2019 (COVID-19) pandemic has overwhelmed
the capacity of healthcare resources and posed a challenge for worldwide hospitals. The …
the capacity of healthcare resources and posed a challenge for worldwide hospitals. The …
A two-gene marker for the two-tiered innate immune response in COVID-19 patients
H Lei - PLoS One, 2023 - journals.plos.org
For coronavirus disease 2019 (COVID-19), a pandemic disease characterized by strong
immune dysregulation in severe patients, convenient and efficient monitoring of the host …
immune dysregulation in severe patients, convenient and efficient monitoring of the host …
Building the model: challenges and considerations of developing and implementing machine learning tools for clinical laboratory medicine practice
Context.—Machine learning (ML) allows for the analysis of massive quantities of high-
dimensional clinical laboratory data, thereby revealing complex patterns and trends. Thus …
dimensional clinical laboratory data, thereby revealing complex patterns and trends. Thus …
Identification of persistent and resolving subphenotypes of acute hypoxemic respiratory failure in two independent cohorts
NA Sathe, LR Zelnick, C Mikacenic, ED Morrell… - Critical Care, 2021 - Springer
Background Acute hypoxemic respiratory failure (HRF) is associated with high morbidity and
mortality, but its heterogeneity challenges the identification of effective therapies. Defining …
mortality, but its heterogeneity challenges the identification of effective therapies. Defining …