IEEE transactions on bio-medical engineering
Apr 1, 2026
OBJECTIVE: Accurate preoperative planning for dental implants, especially in edentulous or partially edentulous patients, relies on precise localization of radiographic templates that guide implant positioning. By wearing a patient-specific radiograp... read more
Diabetic retinopathy (DR), the most prevalent microvascular complication of diabetes mellitus, is the leading cause of irreversible vision loss in the global working-age population. At present, deep learning-integrated ultra-wide-field (UWF) image an... read more
Genome annotation currently requires performing dozens of molecular assays in hundreds of cell and tissue samples, an expensive endeavor which is impractical to replicate across all species and conditions of interest. Here, we introduce BioSeq2Seq, a... read more
Recently, topological deep learning (TDL), which integrates algebraic topology with deep neural networks, has achieved significant success in processing point-cloud data and has emerged as a promising paradigm in data science. However, TDL has not be... read more
LiNO3-based high-temperature phase change materials (PCMs), owing to their specific advantages, e.g., high thermal stability and high latent heat, have been recognized as promising candidates for mitigating or preventing thermal runaway in lithium-io... read more
Journal of chemical information and modeling
Apr 1, 2026
Reticular materials have come to the fore of chemistry with exceptional potential in applications ranging from CO2 capture and chemical separations to catalysis and drug delivery. However, due to the vast combinatorial space of molecular building blo... read more
Giant cell arteritis (GCA) is a systemic vasculitis that predominantly affects mediumand large-sized arteries. Delayed diagnosis may result in irreversible blindness or stroke. Temporal artery biopsy (TAB), historically regarded as the diagnostic gol... read more
Journal of the American Chemical Society
Apr 1, 2026
The vast reaction data within scientific literature represents a rich resource for training predictive machine learning models. However, this resource is fundamentally compromised by a pervasive selection and reporting bias, resulting in imbalanced d... read more
OBJECTIVE: To address the calibration and procedural challenges inherent in remote audiogram assessment for rehabilitative audiology, this study investigated whether calibration-independent adaptive categorical loudness scaling (ACALOS) data can be u... read more
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