Confidence-weighted integration of human and machine judgments for superior decision-making [0.03%]
基于人类和机器判断的自信加权集成决策方法
Felipe Yáñez,Xiaoliang Luo,Omar Valerio Minero et al.
Felipe Yáñez et al.
Large language models (LLMs) can surpass humans in certain forecasting tasks. What role does this leave for humans in the overall decision process? One possibility is that humans, despite performing worse than LLMs, can still add value when...
Contrastive learning enables epitope overlap predictions for targeted antibody discovery [0.03%]
对比学习能够进行表位重叠预测以发现目标抗体
Clinton M Holt,Alexis K Janke,Parastoo Amlashi et al.
Clinton M Holt et al.
Computational epitope prediction remains an unmet need for therapeutic antibody development. We present three complementary approaches for predicting epitope relationships from antibody sequences. First, by analyzing approximately 18 millio...
Michael F Gensheimer
Michael F Gensheimer
Many oncology predictive models fail to improve care. Issues include risks of bias, underpowered radiomics studies, and limited clinical impact. A path forward involves an emphasis on clinically actionable questions, rigor, and generalizabi...
Embeddings from language models are good learners for single-cell data analysis [0.03%]
语言模型嵌入是单细胞数据分析的良好学习器
Tianyu Liu,Tianqi Chen,Wangjie Zheng et al.
Tianyu Liu et al.
Foundation models (FMs) have been built to analyze single-cell data with different degrees of success. Here, we present scELMo (single-cell embedding from language models), a method for analyzing single-cell data with the help of large lang...
A self-supervised framework for emphysema anomaly detection and staging in computed tomography scans [0.03%]
一种自我监督的框架用于计算机断层扫描中的肺气肿异常检测和分期
Xiang Zhang,Mingyue Zhao,Fei Yao et al.
Xiang Zhang et al.
Emphysema, a diffuse and heterogeneous phenotype of chronic obstructive pulmonary disease (COPD), carries substantial morbidity and elevates lung cancer risk. While computed tomography (CT) aids in detection and monitoring, current deep lea...
Leveraging protein language models and a scoring function for indel characterization and transfer learning [0.03%]
利用蛋白质语言模型和评分函数进行插入删除特征分析和迁移学习
Oriol Gracia Carmona,Vilde Leipart,Gro V Amdam et al.
Oriol Gracia Carmona et al.
Protein language models (PLMs) are increasingly used to assess the impact of genetic variants, achieving high accuracy and often outperforming traditional pathogenicity predictors. They enable zero-shot inference, making predictions without...
Alan W Freeman
Alan W Freeman
Deep neural networks (DNNs) are practical and effective but, despite the name, they lack biological validity. The recent study by Kang et al.1 in Patterns takes a step toward rectifying this deficit by hard-wiring receptive fields into the ...
Prewired static visual receptive fields for environment-agnostic perception [0.03%]
环境无关感知的预设静态视觉接受场
Minjun Kang,Seungdae Baek,Se-Bum Paik
Minjun Kang
Biological brains can effortlessly adapt to continuously changing stimulus environments, whereas conventional deep neural networks (DNNs) remain highly susceptible to domain shifts. Here, we demonstrate that static, hard-wired receptive fie...
IoT-LLM: A framework for enhancing large language model reasoning from real-world sensor data [0.03%]
IoT-LLM：一种利用现实世界传感器数据增强大语言模型推理的框架
Tuo An,Yunjiao Zhou,Han Zou et al.
Tuo An et al.
Large language models (LLMs) excel in textual tasks but often struggle with physical-world reasoning tasks. Inspired by human cognition-where perception is fundamental to reasoning-we explore augmenting LLMs with enhanced perception abiliti...
Detecting clinically relevant topological structures in multiplexed spatial proteomics using TopKAT [0.03%]
使用TopKAT在多路复用空间蛋白质组学中检测临床相关的拓扑结构
Sarah Samorodnitsky,Katie Campbell,Amarise Little et al.
Sarah Samorodnitsky et al.
Multiplexed spatial proteomics profiling platforms expose the intricate geometric structure of cells in the tumor microenvironment (TME). The spatial arrangement of cells has been shown to have important clinical implications, correlating w...