Benchmarking the robustness of the correct identification of flexible 3D objects using common machine learning models [0.03%]
基于常见机器学习模型的柔性三维物体正确识别鲁棒性基准测试
Yang Zhang,Andreas Vitalis
Yang Zhang
True three-dimensional (3D) data are prevalent in domains such as molecular science or computer vision. In these data, machine learning models are often asked to identify objects subject to intrinsic flexibility. Our study introduces two da...
PhosNetVis: A web-based tool for fast kinase-substrate enrichment analysis and interactive 2D/3D network visualizations of phosphoproteomics data [0.03%]
PhosNetVis：一种基于Web的工具，可实现快速激酶-底物富集分析和磷酸蛋白质组学数据的交互式二维/三维网络可视化
Osho Rawal,Berk Turhan,Irene Font Peradejordi et al.
Osho Rawal et al.
Protein phosphorylation involves the reversible modification of a protein (substrate) residue by another protein (kinase). Liquid chromatography-mass spectrometry studies are rapidly generating massive protein phosphorylation datasets acros...
Andrew L Hufton
Andrew L Hufton
Wentao Jiang,Heng Yuan,Wanjun Liu
Wentao Jiang
Neuron signal activation is at the core of deep learning and broadly impacts science and engineering. Despite growing interest in neuron cell stimulation via amplitude current, the activation mechanism of biological neurons has limited appl...
Libo Qin,Qiguang Chen,Yuhang Zhou et al.
Libo Qin et al.
Multilingual large language models (MLLMs) leverage advanced large language models to process and respond to queries across multiple languages, achieving significant success in polyglot tasks. Despite these breakthroughs, a comprehensive su...
An objective quantitative diagnosis of depression using a local-to-global multimodal fusion graph neural network [0.03%]
基于局部到整体多模态融合图神经网络的抑郁症客观量化诊断方法
Shuyu Liu,Jingjing Zhou,Xuequan Zhu et al.
Shuyu Liu et al.
This study developed an artificial intelligence (AI) system using a local-global multimodal fusion graph neural network (LGMF-GNN) to address the challenge of diagnosing major depressive disorder (MDD), a complex disease influenced by socia...
The recent Physics and Chemistry Nobel Prizes, AI, and the convergence of knowledge fields [0.03%]
近期的物理和化学诺贝尔奖、人工智能以及知识领域的汇聚
Charles H Martin,Ganesh Mani
Charles H Martin
This article examines the convergence of physics, chemistry, and artificial intelligence (AI), highlighted by recent Nobel Prizes. It traces the historical development of neural networks, emphasizing interdisciplinary research's role in adv...
Decorrelative network architecture for robust electrocardiogram classification [0.03%]
一种鲁棒的动态心电图分类去相关网络架构
Christopher Wiedeman,Ge Wang
Christopher Wiedeman
To achieve adequate trust in patient-critical medical tasks, artificial intelligence must be able to recognize instances where they cannot operate confidently. Ensemble methods are deployed to estimate uncertainty, but models in an ensemble...
Chaochao Chen,Xiaohua Feng,Yuyuan Li et al.
Chaochao Chen et al.
As the parameter size of large language models (LLMs) continues to expand, there is an urgent need to address the scarcity of high-quality data. In response, existing research has attempted to make a breakthrough by incorporating federated ...
Cross-modal contrastive learning for unified placenta analysis using photographs [0.03%]
用于统一胎盘分析的跨模式对比学习（基于照片）
Yimu Pan,Manas Mehta,Jeffery A Goldstein et al.
Yimu Pan et al.
The placenta is vital to maternal and child health but often overlooked in pregnancy studies. Addressing the need for a more accessible and cost-effective method of placental assessment, our study introduces a computational tool designed fo...