AD is a progressive neurodegenerative disorder characterized by memory loss. Due to the advancement in next-generation sequencing, an enormous amount of AD-associated genomics data is available. However, the information about the involvement of these...
Innovation is currently driving enhanced performance and productivity across various fields through process automation. However, identifying intricate details in images can often pose challenges due to morphological variations or specific conditions....
Our algorithmic understanding of vision has been revolutionized by a reverse engineering paradigm that involves building artificial systems that perform the same tasks as biological systems. Here, we extend this paradigm to social behavior. We embodi...
BACKGROUND: Previous efforts to apply machine learning-based natural language processing to longitudinally collected social media data have shown promise in predicting suicide risk.
BACKGROUND: While deep learning classifiers have shown remarkable results in detecting chest X-ray (CXR) pathologies, their adoption in clinical settings is often hampered by the lack of transparency. To bridge this gap, this study introduces the neu...
Journal of computer-aided molecular design
Dec 5, 2024
Molecular machine learning (ML) has proven important for tackling various molecular problems, such as predicting molecular properties based on molecular descriptors or fingerprints. Since relatively recently, graph neural network (GNN) algorithms hav...
IEEE journal of biomedical and health informatics
Dec 5, 2024
There are relatively few studies on the multi-coil reconstruction task of existing Magnetic Resonance Imaging (MRI) methods, as there are problems with insufficient reconstruction details, high memory occupation during training, etc. Therefore, a new...
IEEE journal of biomedical and health informatics
Dec 5, 2024
Drug-drug interaction (DDI) can trigger many adverse effects in patients and has emerged as a threat to medicine and public health. Therefore, it is important to predict potential drug interactions since it can provide combination strategies of drugs...
IEEE journal of biomedical and health informatics
Dec 5, 2024
Medical image segmentation is a fundamental task in many clinical applications, yet current automated segmentation methods rely heavily on manual annotations, which are inherently subjective and prone to annotation bias. Recently, modeling annotator ...
IEEE journal of biomedical and health informatics
Dec 5, 2024
Self-supervised learning (SSL) is a challenging task in sleep stage classification (SSC) that is capable of mining valuable representations from unlabeled data. However, traditional SSL methods typically focus on single-view learning and do not fully...
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