Tuberculosis (TB) remains a major global health challenge, causing approximately 1.4 million deaths annually. In many high-burden regions, limited access to expert radiological interpretation leads to delayed or missed diagnoses. To address this, we ...
BACKGROUND: Cardiac arrest (CA), characterized by an extremely high mortality rate, remains one of the most pressing global public health challenges. It not only causes a substantial strain on health care systems but also severely impacts individual ...
Tabular data is the predominant format for statistical analysis and machine learning across domains such as finance, biomedicine, and environmental sciences. However, conventional methods often face challenges when dealing with high dimensionality an...
Deep Reinforcement Learning (DRL) shows good performance for optimizing battery energy storage systems (BESS) coordinated operations with photovoltaic plants (PV), yet most studies rely on simulations. Bridging the gap to practical application requir...
Fatigue-induced degradation in Carbon Fiber Reinforced Polymer (CFRP) structures poses a critical challenge in long-term structural health monitoring (SHM) applications. In this study, a hybrid deep learning framework is proposed for fatigue state cl...
Characterizing the tumor immune microenvironment from histopathological images offers opportunities for ex vivo immune profiling and prognostic assessment. However, the TCGA-LIHC dataset lacks direct immune cell composition data. Therefore, this stud...
Cancer remains a life-threatening global challenge, with lung cancer ranking among the most devastating forms, impacting millions annually. Early detection and accurate classification are essential for improving patient survival rates, and computed t...
Recent breakthroughs in protein structure prediction have opened new avenues for genome-wide drug discovery, yet existing virtual screening methods remain computationally prohibitive. We present DrugCLIP, a contrastive learning framework that achieve...
Journal of cancer research and clinical oncology
Jan 8, 2026
PURPOSE: Multidisciplinary team (MDT) consultations are crucial for managing pulmonary nodules, yet face challenges in efficiency, evidence-based decision support, and data utilization within the MDT process. We present an integrated artificial intel...
Artificial intelligence (AI) has become a transformative tool in cell biology, driving discoveries through the analysis of complex biological data. This review explores the diverse applications of AI, including its impact on microscopy, imaging, drug...
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