To develop and validate a machine-learning (ML) model that pre-operatively predicts cerebrospinal-fluid leakage (CSFL) after posterior decompression for thoracic ossification of the ligamentum flavum (TOLF), and to elucidate the key risk factors driv...
The soil microbiome plays a crucial role in maintaining healthy ecosystems and supporting sustainable agriculture. Studying its biogeographical structure and distribution is essential for understanding the rates and mechanisms of microbially mediated...
Continuous adult hippocampal neurogenesis is involved in memory formation and mood regulation but is challenging to study in humans. Difficulties finding proliferating progenitor cells called into question whether and how new neurons may be generated...
PURPOSE OF REVIEW: This review explores how artificial intelligence can help advance clinical nutrition and address nutrition education and practice challenges. It highlights the role of AI, mainly through advanced clinical decision-making using gene...
BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) is a prevalent respiratory condition often accompanied by depression, which exacerbates disease burden and impairs quality of life. Early identification of depression risk in COPD patients rema...
Quantum annealing has garnered significant attention as meta-heuristics inspired by quantum physics for combinatorial optimization problems. Among its many applications, nonnegative/binary matrix factorization stands out for its complexity and releva...
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Jul 2, 2025
Breast cancer remains a global health challenge, with an increasing number of cases necessitating innovative approaches to streamline patient management prior to treatment. In this study, we present a comprehensive aptamer-involved surface-enhanced R...
OBJECTIVE: To investigate the effect of manual acupuncture manipulations (MAMs) on subcutaneous muscle tissue, by developing quantitative models of "lifting and thrusting" and "twisting and rotating", based on machine learning techniques.
This study presents a novel approach for real-time gas identification at room temperature. We use UV-modulated Sb-doped SnO sensors combined with machine learning. Our method exclusively employs the gas response () as the sole metric. This eliminates...
Traditional immunochromatographic test strips face significant limitations in detecting trace levels of O157:H7 due to insufficient sensitivity and reliability. To address this challenge, we developed a novel "three-In-One" nanoplatform based on mag...
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