Latest AI and machine learning research in surveys for healthcare professionals.
The generalization problem is broadly recognized as a critical challenge in detecting deepfakes. Most previous work believes that the generalization gap is caused by the differences among various forgery methods. However, our investigation reveals that the generalization issue can still occur when forgery-irrelevant factors shift. In this work, we identify two biases that detectors may also be p...
Causal machine learning (ML) methods hold great promise for advancing precision medicine by estimating personalized treatment effects. However, their reliability remains largely unvalidated in empirical settings. In this study, we assessed the internal and external validity of 17 mainstream causal heterogeneity ML methods -- including metalearners, tree-based methods, and deep learning methods -...
Retrieval-augmented generation (RAG) improves large language models (LLMs) by using external knowledge to guide response generation, reducing halluc...
Visual Question Answering (VQA) is an evolving research field aimed at enabling machines to answer questions about visual content by integrating ima...
This article investigates the critical issue of dataset bias in medical imaging, with a particular emphasis on racial disparities caused by uneven p...
Efficient global Internet scanning is crucial for network measurement and security analysis. While existing target generation algorithms demonstrate...
Neural representation for video (NeRV), which employs a neural network to parameterize video signals, introduces a novel methodology in video repres...
Background: Late Gadolinium Enhancement (LGE) imaging is the gold standard for assessing myocardial fibrosis and scarring, with left ventricular (LV...
Large language models (LLMs) are increasingly attracting the attention of healthcare professionals for their potential to assist in diagnostic asses...
In psychological practice, standardized questionnaires serve as essential tools for assessing mental constructs (e.g., attitudes, traits, and emotio...
Humans seamlessly process multi-voice music into a coherent perceptual whole. Yet the neural strategies supporting this experience remain unclear. One...
Viruses pose a significant threat to global health due to their rapid evolution, adaptability, and increasing potential for cross-species transmission...
Cognitive models are widely used in psychology and neuroscience to formulate and test hypotheses about cognitive processes. These processes are charac...
The free-energy principle has been proposed as a unified theory of brain function, and recent evidence from in vitro experiments supports its validity...
Cognitive flexibility, the ability to adapt behavior in response to changing contingencies, is a key component of adaptive decision-making and is impa...
Ecological interactions, such as predation, are fundamental events that underlie the flow and distribution of energy through food webs. Yet, directly ...
Achieving real-time control of genetic systems is critical for improving the reliability, efficiency, and reproducibility of biological research and e...
The application of artificial intelligence (AI)/machine learning (ML) to MRI can be a powerful tool to streamline clinical decision-making, yet variab...
Molecular diffusion models suffer from systematic sampling biases that prevent optimal structure formation, resulting in chemically suboptimal molecul...
Human behavior arises from the continuous transformation of sensory input into goal-directed actions. While existing analytical methods often break ti...