Yasushi Okochi,Takaaki Matsui,Shunta Sakaguchi et al.
Yasushi Okochi et al.
Mutant analysis is the core of biological/pathological research, and measuring spatial transcriptomes can facilitate the understanding of the disorganized tissue phenotype. However, the high cost and technical challenges of spatial transcri...
Xundong Wu,Pengfei Zhao,Zilin Yu et al.
Xundong Wu et al.
Why have modern artificial neural networks not adopted the nonlinear dendritic structures found in biological brain cells, and what is the core advantage of such active dendritic units? While early studies suggested that dendritic nonlinear...
Erratum: Agentic AI as a coordination paradigm in digital health and agri-food systems [0.03%]
订正：数字健康和农业食品系统中代理式人工智能的协调范式
Anand K Gavai,Miranda P M Meuwissen
Anand K Gavai
[This corrects the article DOI: 10.1016/j.patter.2026.101496.]. © 2026 The Author(s).
Published Erratum
Patterns (New York, N.Y.). 2026 May 13;7(6):101584. DOI:10.1016/j.patter.2026.101584 2026
Spacing effect improves generalization in biological and artificial systems [0.03%]
间歇效应有助于生物和人工系统的泛化能力提升
Guanglong Sun,Ning Huang,Hongwei Yan et al.
Guanglong Sun et al.
Generalization is a fundamental criterion for evaluating learning effectiveness, a domain where biological intelligence excels yet artificial intelligence faces challenges. In biological learning and memory, the well-documented spacing effe...
A multi-modal foundation model for brain disease diagnosis and medical imaging [0.03%]
一种用于脑疾病诊断和医学影像的多模态基础模型
Guoxun Zhang,Zebin Gao,Caohui Duan et al.
Guoxun Zhang et al.
The precise and comprehensive diagnosis of complex brain disorders relies on non-invasive computed tomography (CT) and magnetic resonance imaging (MRI) in conjunction with multi-modal clinical information. Here, we present Brainfound, a mul...
DuoMod-Net: Logarithmic balancing and geometric refinement for imbalanced semi-supervised medical image segmentation [0.03%]
DuoMod-Net：不平衡的半监督医学图像分割的对数平衡和几何细化
Wang Bo,Along He,Ting Xue et al.
Wang Bo et al.
Class imbalance in semi-supervised medical image segmentation poses a dual challenge: it not only compromises feature learning for tail classes but also introduces significant bias in loss gradients toward the predominant background class. ...
SelfCheck-Eval: A multi-module framework for zero-resource hallucination detection in large language models [0.03%]
SelfCheck-Eval：一种用于大型语言模型零资源幻觉检测的多模块框架
Diyana Muhammed,Giusy Giulia Tuccari,Gollam Rabby et al.
Diyana Muhammed et al.
Large language models (LLMs) have achieved considerable progress across diverse applications, yet their tendency to generate incorrect or fabricated content, commonly termed hallucinations, remains a fundamental obstacle to reliable deploym...
Are diffusion models ready for materials discovery in unexplored chemical space? [0.03%]
扩散模型准备好用于探索未知化学空间的材料发现了吗？
Sanghyun Kim,Gihyeon Jeon,Seungwoo Hwang et al.
Sanghyun Kim et al.
While diffusion models are attracting increasing attention for materials discovery, their ability to generate low-energy structures in unexplored chemical spaces has not been systematically assessed. Here, we evaluate the performance of the...
Bridging annotated microscopy imaging data and analysis method development for scientific discovery [0.03%]
连接注释的显微图像数据和分析方法开发以促进科学发现
Kevin A Yamauchi,Virginie Uhlmann
Kevin A Yamauchi
While modern imaging technologies offer unprecedented opportunities to observe life across scales, distilling an understanding of the underlying biological processes from these complex, high-dimensional data remains challenging. Computation...
Abdullah Hasan Safir,Alan F Blackwell,Ramit Debnath
Abdullah Hasan Safir
Hintze et al.'s recent study highlights the tendency of current-generation vision-language models to converge on overly generic outputs. We argue that considering AI imageries as epistemic artefact and AI-driven artistic practices as socio-...