Cardiac activity monitoring is important for assessing cardiovascular status and supporting computational analysis of heart-rate pattern variations from wearable PPG signals. The development of wearable devices and public datasets has made continuous... read more
Endometrial carcinoma (EC) incidence is increasing, with diabetes mellitus (DM) elevating EC risk. This study investigates the glycometabolism-associated gene GCNT3 in EC. We systematically integrated pancreatic tissue DM datasets (GSE25724, GSE76896... read more
The process of migration of IoMT systems in healthcare into post-quantum cryptographic systems is expected to be a gradual one. Here, existing ECC-based devices alongside newly developed quantum-resistant devices will be operating within the same hea... read more
Bufalin, a main active monomer component extracted from the Traditional Chinese Medicine toad venom, exhibits potent anti-tumour activity across diverse malignancies. However, its specific molecular targets in Oesophageal squamous cell carcinoma (ESC... read more
In response to the issue of total interference suppression in space flexible manipulator systems, a state estimation and dynamic compensation cooperative sliding mode control strategy is proposed, based on a neural network-based disturbance observer ... read more
Venous thromboembolism (VTE) is a leading cause of preventable death among patients undergoing systemic treatment for cancer. Studies suggest that treatment strategies such as direct oral anticoagulant administration can significantly reduce the like... read more
DNA functional group classification across species plays a crucial role in understanding genetic diversity, evolutionary relationships and biological function. The increasing availability of genomic data has led to the use of machine learning and dee... read more
There are large variations in how individual patients respond to allergen immunotherapy (AIT) against grass and/or birch allergy. There are currently no reliable biomarkers to predict which patients are likely to benefit from the treatment. The purpo... read more
Adaptive deep brain stimulation (aDBS) has enabled machine learning models to track motor states from neural signals with improved accuracy, aiming to provide electrical stimulation accordingly. Such data-driven techniques necessitate extensive user-... read more
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