Early detection of pain, stress, or hemodynamic instability is key to preventing serious clinical events. In recent years, non-invasive sensors and deep learning algorithms have gained relevance as tools for accurate and continuous monitoring. To map... read more
Due to their position-dependent admixture of the exact-exchange (EXX) energy density, local hybrid functionals (LHs) enable a flexible balance between reduced self-interaction errors and smaller static-correlation errors, allowing an escape from the ... read more
BACKGROUND: Intra-operative identification of parathyroid glands might be technically challenging and is a major source of hypocalcemia and nerve injury. Artificial-intelligence (AI)-based computer-vision systems have emerged as a potential adjunct. ... read more
Current problems in diagnostic radiology
Jan 30, 2026
INTRODUCTION: Recent advancements in Artificial Intelligence (AI)-driven algorithms have improved patient alignment in Computed Tomography (CT) imaging. However, studies mainly focus on single scanners or specific body areas, indicating a need for br... read more
Food research international (Ottawa, Ont.)
Jan 30, 2026
Edible seaweed subcategorized into Chlorophyta (green algae), Phaeophyceae (brown algae) and Rhodophyta (red algae) are considered sustainable functional foods with marketing challenges and regulatory issues. Seaweed-associated safety concerns contin... read more
RATIONALE & OBJECTIVE: Nearly 20% of deceased donor kidneys in the United States are placed "out-of-sequence" (ie, outside of standard allocation rules). The rationale for out-of-sequence placements is to expedite placement of kidneys at risk of nonu... read more
BACKGROUND: Large language models, such as ChatGPT (cGPT), are being integrated increasingly into clinical workflows and medical education. However, concerns persist regarding their susceptibility to bias, especially in high-stakes areas like pain ma... read more
Efficient waste sorting is crucial for enabling circular-economy practices and resource recovery in smart cities. This paper evaluates both traditional machine-learning (Random Forest, SVM, AdaBoost) and deep-learning techniques including custom CNNs... read more
Despite progress in Large Vision Language Models (LVLMs), object hallucination remains a critical issue in image captioning task, where models generate descriptions of non-existent objects, compromising their reliability. Previous work attributes thi... read more
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