Parkinson's disease (PD) causes motor, non-motor, and mental health challenges that significantly impact health-related quality of life (HRQoL); however, previous studies relied on subjective assessments. Several factors are associated with poor HRQo...
The decision-making process in healthcare services encounters numerous challenges. Artificial intelligence (AI) has significantly contributed to enhancing healthcare decision-making. There is a lack of validated instruments available in the literatur...
Soft Tissue sarcomas (STS) are a group of heterogeneous and complex diseases where being able to predict the appearance of metastases is key to inform clinical decisions, especially the prescription of adjuvant chemotherapy. We developed SarcNet: a m...
Accurate preoperative glioma grading remains a critical challenge in neuro-oncology. This study presents a novel integrated approach combining deep learning architectures with radiomics features derived from multi-parametric MRI to improve preoperati...
Continuous kidney replacement therapy (CKRT) is an essential treatment for uncontrolled severe metabolic acidosis. However, CKRT can increase workload and lead to complications, thus necessitating its selective application to patients who stand to be...
Alpha-thalassemia is a widespread genetic disorder, and accurately distinguishing between alpha-plus (α⁺) and alpha-zero (α⁰) types is critical for effective screening and management. This study developed and evaluated machine learning models to clas...
Respiratory ailments constitute various pathological conditions affecting the respiratory system, including the airways, pulmonary tissues, and associated structures. When these conditions are left untreated or inadequately managed, they can result i...
In recent years, Hand Gesture Recognition (HGR) devices have been designed to recognize gestures in real time using machine-learning classifiers (MLCs). However, the performance of these classifiers heavily relies on the tuning of their hyperparamete...
Neural decoding of speech intention could advance the development and application of brain-computer interface (BCI) technology. Currently, lack of dataset limited the research on decoding the true speech intention, especially the diverse intentions e...
Improving language learning through a better understanding of how brain activity and emotional intelligence interact is a promising research direction with practical value in education. Traditional methods in this area often use static models, which ...
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