Latest AI and machine learning research in pain management for healthcare professionals.
Lewy body dementia (LBD), which encompasses Parkinson's disease dementia (PDD) and Dementia with Lewy bodies (DLB), lacks established biofluid markers of its complex clinical and neuropathological heterogeneity. Multiplex proteomic tools, such as the recently developed NUcleic acid Linked ImmunoSandwich Assay (NULISA), can assess a diverse array of neurodegenerative targets and address these bioma...
Background: Wearable technologies enable scalable and continuous monitoring of emotional states through passive sensing of physiological and behavioral signals. However, conventional learning approaches often struggle to model the complex temporal, contextual, and relational dependencies underlying human emotions. To address these limitations, we propose a graph-based framework that represents mul...
Objective: Stigmatizing language in the electronic health record (EHR) has been associated with adverse patient experience in substance use disorder c...
Neuroimaging based pain decoding faces two underappreciated challenges: between subject variability that prevents classifiers from generalizing across...
Machine learning is increasingly applied to species-level biological data, but phylogenetic autocorrelation can make evaluation species statistically ...
Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the leading cause of dementia, affecting memory, reasoning, communication, an...
While multimodal data integrating diverse imaging and clinical tabular records is crucial for accurate medical diagnosis, the arbitrary absence of spe...
High-fidelity 3D Gaussian head avatar generation is critical for applications such as AR/VR, telepresence, and digital humans. Existing methods depend...
Accurate in vivo prediction of neuropathology is critical for advancing diagnosis and treatment of Alzheimer's disease and related dementias (ADRDs). ...
Migraine detection and sentiment analysis in healthcare have become increasingly important, particularly with the rise of social media platforms like ...
Background. This study examines a competition based model (Cmodel) designed to capture the temporal dynamics of successive brain microstates derived f...
Importance: Abdominal pain causes roughly 10 million US emergency department (ED) visits annually, most resulting in discharge. Post-discharge courses...
Background: Heterogeneity in symptom presentation and treatment response in irritable bowel syndrome (IBS) remains poorly understood. The gut microbio...
Machine learning is accelerating biomedical research. Cross-validation is widely used to compare predictive performance -- not only to benchmark algor...
Functional magnetic resonance imaging (fMRI) data are inherently complex, characterized by high dimensionality, intricate inter-regional dependencies,...
Whether individual transcripts carry intrinsic features that predetermine their response to external perturbations is unknown. Here we used nanopore d...
Background and Objectives Patients with peripheral neuropathies (PN) commonly exhibit balance impairment. In clinical practice, balance is typically a...
Drug-drug interaction (DDI) prediction is a critical task in computational biomedicine, as adverse interactions between co-administered drugs can caus...
Many multimodal learning tasks require supervision that remains consistent across edits, viewpoints, and scene-level interventions. However, such supe...
Randomized neural networks (RdNNs) enable efficient, backpropagation-free training by freezing randomly initialized input-to-hidden weights, which per...