Cardiac arrhythmias, characterized by irregular heart function, disrupt normal blood circulation and are commonly detected using electrocardiograms (ECGs). ECG is widely preferred due to its cost-effectiveness, ease of application, and high reliabili...
The simultaneous monitoring of both blood glucose level (BGL) and blood pressure (BP) has rarely been studied directly. The exploitation of physiological interactions between them will advance the learning of either task. However, the lack of availab...
Arrhythmia is a prevalent cardiac disorder that can lead to severe complications such as stroke and cardiac arrest. While deep learning has advanced automated ECG analysis, challenges remain in accurately classifying arrhythmias due to signal variabi...
OBJECTIVE: This study aimed to develop an innovative early prediction model for acute kidney injury (AKI) following cardiac surgery in intensive care unit (ICU) settings, leveraging preoperative and postoperative clinical variables, and to identify k...
BACKGROUND: Postoperative complications in colorectal surgery can significantly impact patient outcomes and healthcare costs. Accurate prediction of these complications enables targeted perioperative management, improving patient safety and optimizin...
OBJECTIVE: Multi-institutional datasets are widely used for machine learning from clinical data, to increase dataset size and improve generalization. However, deep learning models in particular may learn to recognize the source of a data element, lea...
Cross-corpus speech emotion recognition (CCSER) aims to develop robust models capable of accurately identifying a speaker's emotional state across diverse datasets. This task is challenged by variations in dataset characteristics, such as differences...
Accurate segmentation of mammographic mass is very important as shape characteristics of these masses play a significant role for radiologist to diagnose benign and malignant cases. Recently, various deep learning segmentation algorithms have become ...
BACKGROUND: Ultrasound-based bone surface segmentation is crucial in computer-assisted orthopedic surgery. However, ultrasound images have limitations, including a low signal-to-noise ratio, acoustic shadowing, and speckle noise, which make interpret...
OBJECTIVE: Major lower extremity amputation for advanced vascular disease involves significant perioperative risks. Although outcome prediction tools could aid in clinical decision-making, they remain limited. To address this, we developed machine le...
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