In recent years， the exploration and development of artificial intelligence （AI） technology in clinical trials for liver diseases have promoted the continuous innovation of research methods and processes in this field. AI has gradually become an important technical tool for various links of clinical trial including patient selection， risk stratification， endpoint evaluation， and result interpretation. Nevertheless， the standardized integration of AI into clinical trials still faces the methodological challenges such as data quality control， model interpretability， and causal inference. From the perspective of methodology， this article systematically reviews the principal application scenarios of AI as an object under investigation （validation trials） and as a research tool （supportive trials） in clinical trials for liver diseases， as well as the major methodological challenges of AI-related clinical trials along and the corresponding solution strategies， in order to provide methodological guidance for promoting the scientific and standardized implementation of AI technologies.

Recording the highly diverse and dynamic activities in large populations of neurons in behaving animals is crucial for a better understanding of how the brain works. To meet this challenge, extensive efforts have been devoted to developing functional fluorescent indicators and optical imaging techniques to optically monitor neural activity. Indeed, optical imaging potentially has extremely high throughput due to its non-invasive access to large brain regions and capability to sample neurons at high density, but the readout speed, such as the scanning speed in two-photon scanning microscopy, is often limited by various practical considerations. Among different imaging methods, light field microscopy features a highly parallelized 3D fluorescence imaging scheme and therefore promises a novel and faster strategy for functional imaging of neural activity. Here, we briefly review the working principles of various types of light field microscopes and their recent developments and applications in neuroscience studies. We also discuss strategies and considerations of optimizing light field microscopy for different experimental purposes, with illustrative examples in imaging zebrafish and mouse brains.
Animals ; Mice ; Microscopy/methods* ; Zebrafish ; Neurons/physiology* ; Brain/physiology* ; Neurosciences