Cross-Anatomy Transfer Versus Sparse Interpolation in Digital-Twin-Oriented Aortic Fluid-Structure Interaction Surrogates
研究通过对比跨解剖结构迁移与稀疏插值方法，评估了主动脉流固耦合代理模型的可信度，发现稀疏插值在场完成上表现更优。
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PRICE: A Systematic Study of LLM Adaptation Choices for Bitcoin Price Forecasting
研究通过PRICE系统方法，采用参数高效微调、低秩适应等技术，解决了使用大型语言模型进行比特币价格短期预测的准确性问题。
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Microlensify: a Transformer Based Machine Learning Classifier for Microlensing Events Trained on TESS Light Curves
研究使用基于Transformer的机器学习分类器Microlensify处理TESS光曲线数据，以识别微引力透镜事件并区分假阳性。
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From Operations to Elderly Care Outcomes: A Thematic Review of Industrial Engineering and Decision-Support Approaches
This study addresses a critical gap in geriatric care research, which has predominantly emphasized operational efficiency while lacking robust connections to clinical health outcomes. Through a systematic review of 30 interdisciplinary studies at the intersection of industrial engineering and operations research applied to elderly care, the work categorizes existing literature into three thematic domains: home-based medical care, polypharmacy management, and chronotherapeutic clinical scheduling. It proposes a novel conceptual framework that explicitly links operational optimization with clinical outcomes, advocating a paradigm shift from isolated task-level improvements toward integrated, multi-layer decision-making. By incorporating human-centered design, systems analysis, and emerging technologies such as digital twins and large language models, the study highlights the field’s current overemphasis on workforce scheduling at the expense of health impact, thereby laying a theoretical and technical foundation for intelligent care decision systems spanning hospital and community settings.
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Cross-Anatomy Transfer Versus Sparse Interpolation in Digital-Twin-Oriented Aortic Fluid-Structure Interaction Surrogates
研究通过对比跨解剖结构迁移与稀疏插值方法，评估了主动脉流固耦合代理模型的可信度，发现稀疏插值在场完成上表现更优。
0 citationsRead paper
Meta-Learning for Classifier Selection in Image Datasets: A Feature-Driven Framework for Accuracy Prediction
本文提出一种元学习框架，通过提取图像数据集的复杂性特征预测分类器性能，以解决图像数据集中选择最优分类器的问题。
0 citationsRead paper
PRICE: A Systematic Study of LLM Adaptation Choices for Bitcoin Price Forecasting
研究通过PRICE系统方法，采用参数高效微调、低秩适应等技术，解决了使用大型语言模型进行比特币价格短期预测的准确性问题。
0 citationsRead paper
Microlensify: a Transformer Based Machine Learning Classifier for Microlensing Events Trained on TESS Light Curves
研究使用基于Transformer的机器学习分类器Microlensify处理TESS光曲线数据，以识别微引力透镜事件并区分假阳性。
0 citationsRead paper
From Operations to Elderly Care Outcomes: A Thematic Review of Industrial Engineering and Decision-Support Approaches
This study addresses a critical gap in geriatric care research, which has predominantly emphasized operational efficiency while lacking robust connections to clinical health outcomes. Through a systematic review of 30 interdisciplinary studies at the intersection of industrial engineering and operations research applied to elderly care, the work categorizes existing literature into three thematic domains: home-based medical care, polypharmacy management, and chronotherapeutic clinical scheduling. It proposes a novel conceptual framework that explicitly links operational optimization with clinical outcomes, advocating a paradigm shift from isolated task-level improvements toward integrated, multi-layer decision-making. By incorporating human-centered design, systems analysis, and emerging technologies such as digital twins and large language models, the study highlights the field’s current overemphasis on workforce scheduling at the expense of health impact, thereby laying a theoretical and technical foundation for intelligent care decision systems spanning hospital and community settings.
0 citationsRead paper