. Deep learning has emerged as a powerful approach for decoding electroencephalography (EEG)-based brain-computer interface (BCI) signals. However, its effectiveness is often limited by the scarcity and variability of available training data. Existin...
Feature selection (FS) is critical for datasets with multiple variables and features, as it helps eliminate irrelevant elements, thereby improving classification accuracy. Numerous classification strategies are effective in selecting key features fro...
Many studies have used images of novel objects as experimental materials. Existing novel object databases do not provide diverse exemplars, and many studies need to manipulate or examine the diversity of exemplars. To fill this gap in experimental ma...
Diabetes is one of the main diseases posing a threat to healthcare systems. One of the complications of diabetes is diabetic retinopathy, which, if left untreated, can lead to serious consequences such as blindness. Early detection of this disease is...
This study introduces a robust and efficient hybrid deep learning framework that integrates Convolutional Neural Networks (CNN) with Bidirectional Long Short-Term Memory (BLSTM) networks for the automated detection and classification of cardiac arrhy...
BACKGROUND: Existing machine learning studies for pneumonia mortality prediction are limited by small sample sizes, single-center designs, and lack of comprehensive external validation across diverse healthcare systems. No previous study has systemat...
BACKGROUND: Sepsis-associated acute kidney injury (SA-AKI) is a frequent and life-threatening complication in patients in the intensive care unit (ICU), significantly increasing both mortality rates and the risk of chronic kidney dysfunction. However...
ChEMBL is a large-scale, open-access, FAIR database of bioactive molecules with drug-like properties. ChEMBL 35 contains 17,500 approved drugs, and drugs that are progressing through the clinical development pipeline. Drug curation has formed an inte...
BACKGROUND: Acute kidney injury (AKI) in patients with liver cirrhosis represents a significant clinical challenge with high mortality rates. This study aimed to develop and validate a machine learning-based prediction model for 28-day mortality in A...
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