Latest AI and machine learning research in critical care for healthcare professionals.
Multi-view multi-label learning (MVML) aims to train a model that can explore the multi-view informa...
Antimicrobial resistance (AMR) is a major threat to public health worldwide. It is a promising way t...
BACKGROUND: Acute heart failure (AHF) in the intensive care unit (ICU) is characterized by its criti...
Over the past decades, massive Electronic Health Records (EHRs) have been accumulated in Intensive C...
OBJECTIVE: To explore the differences and associations of hypoxic parameters among distinct types of...
A multi-objective optimization method based on an injury prediction model is proposed to address the...
Air pollution, particularly PM2.5, has long been a critical concern for the atmospheric environment....
BACKGROUND: Global pediatric healthcare reveals significant morbidity and mortality rates linked to ...
Multi-task learning (MTL) methods are widely applied in breast imaging for lesion area perception an...
The COVID-19 pandemic has altered the circulation of non-SARS-CoV-2 respiratory viruses. In this stu...
Tissue hysteresivity is an important marker for determining the onset and progression of respiratory...
Current research in nephrology is increasingly focused on elucidating the complexity inherent in tig...
Annotating active sites in enzymes is crucial for advancing multiple fields including drug discovery...
The subcellular localization of messenger RNA (mRNA) not only helps us to understand the localizatio...
Synthetic lethality (SL) and synthetic viability (SV) are commonly studied genetic interactions in t...
Viral infections significantly impact the immune system, and impact will persist until recovery. How...
Background : Extracorporeal membrane oxygenation (ECMO) is an effective technique for providing shor...
For scene matching, the extraction of metric features is a challenging task in the face of multi-sou...
As the global incidence of cancer continues to rise rapidly, the need for swift and precise diagnose...
In multi-view learning, graph-based methods like Graph Convolutional Network (GCN) are extensively r...
Recently, Vision Transformer and its variants have demonstrated remarkable performance on various co...