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基于机器学习预测血糖异常急性缺血性卒中患者预后模型研究 Prediction of Clinical Outcome of Acute Ischemic Stroke Patients with Hyperglycemia Based on Machine Learning Model

open access: yesZhongguo cuzhong zazhi, 2022
目的 建立基于机器学习的血糖异常急性缺血性卒中患者的预后预测模型,比较传统logistic模型与机器学习模型的预测效能。 方法 以中国国家卒中登记研究Ⅲ(China national stroke registration study III,CNSR-Ⅲ)血糖异常急性缺血性卒中患者为研究对象,采用病例报告表收集患者的人口学信息、既往病史、实验室检查、头颅影像学检查、卒中病因分型等临床资料。采用分层10折交叉验证划分训练集(3325例)和测试集(369例),基于随机森林、梯度提升决策树(
杨佳蕾, 陈思玎, 孟霞, 姜勇, 王拥军
doaj   +1 more source

Emerging applications of large language models in ecology and conservation science

open access: yesConservation Biology, EarlyView.
Abstract Large language models (LLMs) mark a major development in artificial intelligence, with potentially transformative implications for ecology and conservation science. Built on advanced deep‐learning architectures, these models can support a wide range of tasks. We reviewed emerging applications of LLMs, drawing on the wider scientific literature
Christos Mammides   +5 more
wiley   +1 more source

机器学习在力学模拟与控制中的应用专题序

open access: yes, 2021
近几年来,随着高性能计算机和大数据科学的快速发展,机器学习方法在各个领域得到了越来越多的应用.力学学科在过去几十年积累了大量的数值模拟数据、实验测量数据和现场监测数据,这些大规模、高维度的数据蕴含了丰富的物理特征,但传统方法无法有效地处理这些庞大的数据群.机器学习方法可以从巨量的数据海洋中挖掘有用的信息,并能为总结新的物理规律提供有效的指导.另一方面,机器学习方法存在着可解释性差、泛化能力弱、容易过拟合等问题.针对基于第一性原理的力学问题开展机器学习研究,并和已知的物理规律相对照 ...
晋国栋, 王建春
core  

MBR中膜污染的人工神经网络预测研究进展

open access: yesGongye shui chuli, 2022
膜生物反应器(MBR)作为一种新型废水处理技术在污水处理方面具有广阔的应用前景。但是,膜污染是制约MBR进一步发展的瓶颈性问题。近年来,随着数学算法及计算机技术的发展,将人工神经网络(ANN)等机器学习算法应用于MBR的膜污染预测成为研究的热点。总结了膜污染的影响因素,探讨了基于经典数学模型膜污染预测的优缺点,综述了近年来国内外学者运用简单ANN、优化算法ANN和深度学习ANN对MBR膜污染预测的研究,提出优化算法ANN与深度学习ANN在面对复杂环境下更具优势。此外 ...
张浩良   +4 more
doaj  

Artificial Intelligence for Language Learning: A Systematic Review of its Design, Theoretical Foundations, Implementation, and Impact

open access: yesInternational Journal of Applied Linguistics, EarlyView.
ABSTRACT Although the use of AI technologies (e.g., chatbots and automated writing evaluations (AWE)) has gained considerable attention in language learning fields in recent years, how AI technologies have been designed and implemented in language learning education, as well as their effectiveness, is understudied.
Shen Qiao   +2 more
wiley   +1 more source

How Do I Measure up? Social Influence and L2 Motivation in the Algorithmic Age

open access: yesInternational Journal of Applied Linguistics, EarlyView.
ABSTRACT Comparative thinking is a fundamental human drive and a hallmark of contemporary life. For social action, such as the learning and use of additional languages, a target for appraisal (an L2 attribute) is evaluated in relation to a comparison standard (an appraiser's standpoint).
Alastair Henry, Meng Liu
wiley   +1 more source

机器学习在脑血管病基因组学数据分析中的应用进展 Application of Machine Learning in Genomic Data Analysis of Cerebrovascular Diseases

open access: yesZhongguo cuzhong zazhi, 2023
随着精准医疗时代的到来,在脑血管病领域,基因组学研究受到越来越多的关注。基因组学数据的高维复杂性,使得机器学习成为分析基因组学数据的最为有效的工具之一。本文对机器学习的基本概念、主要步骤、算法分类以及各算法在脑血管病领域基因组学研究中的应用现状进行介绍,以期为未来脑血管病基因组学研究提供参考。 Abstract: With the advent of the era of precision medicine, genomics research is gradually gaining ...
姜英玉,陈思玎,仇鑫,谷鸿秋
doaj   +1 more source

Microstructure Engineering Toward High Cost‐Effective Nd–Fe–B Sintered Magnets: A Review

open access: yesRare Metals, Volume 45, Issue 7, July 2026.
ABSTRACT Nd–Fe–B sintered magnets, critical for enhancing electromechanical conversion efficiency and operational stability in wind turbines and electric vehicle drives, are prized for their outstanding coercivity, high remanence, and superior maximum energy product.
Dongmin Zhang   +5 more
wiley   +1 more source

Complete elliptic Fourier descriptor normalization and its application in quantitative morphological analysis

open access: yesMethods in Ecology and Evolution, Volume 17, Issue 7, Page 2123-2134, July 2026.
Abstract Elliptic Fourier analysis (EFA) is often employed in geometric morphometrics (GM), but the normalization of elliptic Fourier descriptor (EFD) has persistently posed challenges for obtaining unique and comparable results, especially in the application of outline‐based GM methods, which limits the implementation in automated analysis of numerous,
Hui Wu   +6 more
wiley   +1 more source

基于半监督学习的人脸识别反欺骗方法研究

open access: yes智能科学与技术学报, 2021
鉴别图像中的真伪人脸是一个长期具有挑战性的问题。当合成的伪造人脸十分逼真时,机器识别难分真假,甚至肉眼也难以区分。基于监督学习的真伪人脸识别建模往往需要大量的标签样本,模型的性能严重依赖样本的规模。提出一种基于半监督学习的人脸识别反欺骗方法,以减少对大量标签样本的依赖。该方法利用图像修复模型来学习人脸图像潜在的数据分布。在训练过程中,少量标签样本周期性地提供有监督信号来训练分类器,以区分真伪人脸。该方法可用于不同场景的伪造人脸,如基于摄像头拍摄的人脸或生成对抗网络生成的人脸。在NUAA ...
李莉, 曾伟良, 黄永慧, 孙为军
doaj  

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