Latest AI and machine learning research in intensivists for healthcare professionals.
Sleep disorder detection has greatly improved with the integration of machine learning, offering enh...
Precise segmentation of retinal vasculature is crucial for the early detection, diagnosis, and treat...
Thoracic Cone-beam computed tomography (CBCT) is routinely collected during image-guided radiation t...
BACKGROUND: Sepsis, a critical global health challenge, accounted for approximately 20% of worldwide...
Multi-view graph refining-based clustering (MGRC) methods aim to facilitate the clustering of data v...
Drug-drug interactions (DDIs) occur when multiple medications are co-administered, potentially leadi...
Since the malignancy of gliomas varies with their grade, classifying gliomas of different grades can...
Sequential recommendation models aim to predict the next item based on the sequence of items users i...
As education increasingly relies on data-driven methodologies, accurately predicting student perform...
BACKGROUND: Sepsis-associated acute kidney injury (S-AKI) has a significant impact on patient surviv...
BACKGROUND & AIMS: Accurate multi-classification is a prerequisite for appropriate management of foc...
As an effective data preprocessing method, feature subset selection has been widely explored in rece...
Algal blooms in freshwater, which are exacerbated by urbanization and climate change, pose significa...
Multi-view learning aims on learning from the data represented by multiple distinct feature sets. Va...
INTRODUCTION: Propofol is a widely used sedative-hypnotic agent for critically ill patients requirin...
OBJECTIVES: To develop a machine learning-based prediction model using clinical data from the first ...
Source-free domain adaptation (SFDA) has become crucial in medical image analysis, enabling the adap...
The inherent variability of lesions poses challenges in leveraging AI in 3D automated breast ultraso...
Multi-view classification integrates features from different views to optimize classification perfor...
While self-labeled methods can exploit unlabeled and labeled instances to train classifiers, they ar...
Long time series forecasting has extensive applications in various fields such as power dispatching,...