Machine learning analyses are widely used for predicting cognitive abilities, yet there are pitfalls that need to be considered during their implementation and interpretation of the results. Hence, the present study aimed at drawing attention to the ...
Human moral interactions often assume that resources should be allocated equitably, i.e., one should not take more than one's fair share. To what extent do people apply this assumption to social AI entities? Using a 21-round Ultimatum Game, we invest...
Subdural hemorrhage (SDH) is a critical condition requiring prompt assessment of its progression using computed tomography (CT). This study aimed to develop a deep-learning model to predict temporal changes in SDH by leveraging Hounsfield Units (HU) ...
Accurate detection, localization, and staging of breast cancer lymph node metastases are critical for guiding treatment decisions and predicting patient outcomes. This study presents a selective neighborhood attention-based deep learning framework th...
Early skin disease detection significantly improves patient survival rates, yet limited access to dermatological expertise creates an urgent need for automated diagnostic systems. In this paper, we develop a dual-branch deep learning framework that s...
Type 2 diabetes mellitus (T2DM) and metabolism-associated fatty liver disease (MAFLD) are prevalent metabolic disorders with shared pathophysiological mechanisms. A comprehensive understanding of the molecular pathways involved in their onset and pro...
Patients undergoing maintenance hemodialysis (MHD) often suffer from sarcopenia, which affects their balance and significantly increases the risk of falls and death. Actively identifying sarcopenia, understanding the relationship between sarcopenia a...
With the rapid development of music streaming platforms, accurate understanding of lyric emotions has become crucial for enhancing personalized services in music recommendation systems. However, existing methods show significant limitations in proces...
The standard assessment of mental health typically involves clinical interviews conducted by highly trained clinicians. While effective, this approach faces substantial limitations, including high costs, high clinician workload, variability in expert...
In recent years, research on the relationship between coagulation system abnormalities and tumor immunity has been widely reported. Bladder cancer (BC), as an immunogenic tumor, holds great promise in immunotherapy. The role of coagulation-related ge...
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