BACKGROUND: The immune microenvironment significantly influences neural regeneration in spinal cord injury (SCI). Lactate activates central nervous system (CNS) glial cells, prompting the secretion of proinflammatory cytokines and triggering an infla...
BACKGROUND: Monitoring intrinsic capacity and implementing appropriate interventions can support healthy aging. There are, though, few tools available for predicting decline in intrinsic capacity among older adults. This study aimed to develop and va...
In modern intensive caged laying hen production, variations in egg-laying time (ELT) among layers often increase the workload for egg collection, thereby raising the costs of labor or power and reducing overall efficiency. For management purpose, ear...
OBJECTIVE: We aimed to develop a machine learning (ML) model to preoperatively predict surgical difficulty for pheochromocytomas and paragangliomas (PPGLs) using clinical and radiomic features.
To explore the capabilities of race/ethnicity and gender prediction algorithms in uncovering patterns of authorship distribution in scientific paper submissions to a major peer-reviewed scientific journal (), we analyzed 17 667 manuscript submissions...
BACKGROUND: People with psychosis have a higher suicide risk than the general population. Natural language processing (NLP) has been used to understand communication in psychosis and suicide risk prediction, but not to predict future suicidal behavio...
OBJECTIVE: Young adults face elevated risks from alcohol use yet encounter significant barriers to accessing evidence-based interventions. Large language models (LLMs) represent a promising advancement for delivering personalized behavioral intervent...
Computer methods and programs in biomedicine
Jul 1, 2025
OBJECTIVES: Achieving efficient analysis of multiple pathological indicators has great significance for breast cancer prognosis and therapeutic decision-making. In this study, we aim to explore a deep multi-task learning (MTL) framework for collabora...
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Jul 1, 2025
PURPOSES: This study aimed to develop a computed tomography (CT)-based multi-organ segmentation model for delineating organs-at-risk (OARs) in pediatric upper abdominal tumors and evaluate its robustness across multiple datasets.
BACKGROUND: The exposome framework seeks to unravel the cumulated effects of environmental exposures on health. However, existing methods struggle with challenges including multicollinearity, non-linearity and confounding. To address these limitation...
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