Sepsis remains a leading cause of mortality worldwide, driven by its clinical complexity and delayed recognition. Artificial intelligence (AI) offers promising solutions to improve sepsis care through earlier detection, risk stratification, and perso...
BACKGROUND: Artificial intelligence (AI) has demonstrated remarkable capabilities across diverse medical applications, potentially revolutionizing healthcare delivery systems. This systematic review and meta-analysis investigated the comparative effe...
Generative Artificial Intelligence (Gen-AI) systems offer significant opportunities for personalized learning in higher education. Studying the effects of personality traits on the use of Gen-AI is crucial for understanding the role of individual dif...
Large language models (LLMs) are the engines behind generative Artificial Intelligence (AI) applications, the most well-known being chatbots. As conversational agents, they-much like the humans on whose data they are trained-exhibit social bias. The ...
Sports teaching in universities relies on staff experience, training modes., evaluated by the student's performance and competitive outcomes. The teaching quality assessment requires a large volume of data related to teaching patterns, training. A Te...
DNA replication stress is a hallmark of cancer that is exploited by chemotherapies. Current assays for replication stress have low throughput and poor resolution whilst being unable to map the movement of replication forks genome-wide. We present a n...
Longitudinal serological proteomic dynamics during antiviral therapy (AVT) in chronic hepatitis B (CHB) patients with liver fibrosis remain poorly characterized. Here, using four-dimensional data-independent acquisition mass spectrometry (4D-DIA-MS),...
Healthcare data protection in our mutually connected era has emerged as an issue of serious concern with private patient information, which has been exposed more often due to data violations and cyber-attacks. Network structures CNN and LSTM as part ...
Distributed Collaborative Machine Learning (DCML) offers a promising alternative to address privacy concerns in centralized machine learning. Split learning (SL) and Federated Learning (FL) are two effective learning approaches within DCML. Recently,...
Immunogenic cell death (ICD) is capable of activating both innate and adaptive immune responses. In this study, we aimed to develop an ICD-related signature in glioma patients and facilitate the assessment of their prognosis and drug sensitivity. Con...
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