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Distinct but correct: generating diversified and entity-revised medical response

Science China(Information Sciences) 2024年第3期67卷 94-113页

作者： Bin LI Bin SUN Shutao LI Encheng CHEN Hongru LIU Yixuan WENG Yongping BAI Meiling HU College of Electrical and Information Engineering Hunan University School of Mathematics Sun Yat-sen University JD Technology National Laboratory of Pattern Recognition Institute of AutomationChinese Academy of Sciences Xiangya Hospital of Central South University teaching and research section of Clinical Nursing Xiangya Hospital of Central South University

Medical dialogue generation(MDG) is applied for building medical dialogue systems for intelligent consultation. Such systems can communicate with patients in real time, thereby improving the efficiency of clinical diagnosis. However, predicting correct entities and correctly generating distinct responses remain a great challenge. Inspired by actual doctors’ responses to patients, we consider MDG a two-stage task: entity prediction and dialogue generation. For entity prediction, we design an ent-mac post pre-training strategy by leveraging external medical entity knowledge to enhance the pre-trained model. For dialogue generation, we propose an entity-aware fusion MDG method in which predicted entities are integrated into the dialogue generation model through different encoding fusion mechanisms, using information from different sources. Because the diverse beam search algorithm can produce responses with entities that deviate from the predicted entities, an entity-revised diverse beam search is proposed to correct the entities entailed in the generated responses and make the generated responses more distinct. The experimental results on the China Conference on Knowledge Graph and Semantic Computing 2021(A/B tests) and the International Conference on Learning Representations 2021(online test) datasets show that the proposed method outperforms several state-of-the-art methods, which demonstrates its practicability and effectiveness.

关键词： medical entity prediction ent-mac post pre-training strategy entity-aware fusion medical dialogue generation encoding fusion mechanism entity-revised diverse beam search

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护士参与抗菌药物管理现状及影响因素研究

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International Journal of Nursing Sciences 2024年第1期11卷 91-98,I0002,I0003页

作者：聂慧宇岳丽青彭欢周金平李冰玉曹紫薇 teaching and research section of Clinical Nursing Xiangya Hospital of Central South UniversityChangshaHunanChina Xiangya School of Nursing Central South UniversityChangshaHunanChina

目的基于能力、机会、动机和行为(capability, opportunity, motivation, and behavior, COM-B )理论,调查我国护士抗菌药物管理(antimicrobial stewardship, AMS)参与水平及其影响因素,为制订有效策略提高AMS护理质量提供参考依据。... 详细信息

目的基于能力、机会、动机和行为(capability, opportunity, motivation, and behavior, COM-B )理论,调查我国护士抗菌药物管理(antimicrobial stewardship, AMS)参与水平及其影响因素,为制订有效策略提高AMS护理质量提供参考依据。方法采用横断面调查法。于2021年11月至2022年1月,选取湖南省的17所三级医院的4514名护士进行调查。在COM-B理论指导下,自行编制护士参与抗菌药物管理问卷(the NurseAMS Engagement Que stionnaire ,NAEQ)。该问卷包括能力(14个条目)、机会(7个条目)、动机(6个条目)和行为(12个条目)4个维度,共39个条目。结果护士NAEQ总分为( 155.08±±27.12)分,得分率为79.5% ,表明护士参与AMS处于中等水平。其中,能力维度得分为(52.33±13.48 )分,机会维度得分为(28.64±5.76)分,动机维度得分为(24.57±4.57)分,行为维度得分为(4953±8.83)分。不同职称、是否兼职感染控制护士、是否知晓AMS团队、是否知晓抗菌药物限定日剂量、科室类型、科室是否配备临床药师、参与抗菌药物培训和医师-护士联合查房的频率等特征不同的护士NAEQ得分比较,差异有统计学意义(P<0.05)。其中初级职称护士的NAEQ得分高于中级职称护士(P<0.05);担任兼职感染控制护士、知晓AMS团队、知晓抗菌药物限定日剂量的护士NAEQ得分高于其他护士(P<0.01);重症监护室和传染病科护士NAEQ得分低于五官科等其他科室的护士(P<0.01);科室配备临床药师的护士NAEQ得分高于未配备或不清楚是否配备临床药师的护士(P<0.01);参与抗菌药物培训和医师-护士联合查房次数较多的护士NAEQ得分高于其他护士(P<0.01)。结论加强教育和培训及改善多学科沟通与协作等多种策略有望提高护士参与AMS的水平。此外,应更多关注中级职称、感染控制经验较少以及特定科室工作的护士。

关键词：抗菌药物管理行为中国医院知识动机护士

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YOLO-Drone:A Scale-Aware Detector for Drone Vision

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Chinese Journal of Electronics 2024年第4期33卷 1034-1045页

作者： Yutong LI Miao MA Shichang LIU Chao YAO Longjiang GUO School of computer Science Shaanxi Normal University Key Laboratory of Modern teaching Technology Ministry of Education College of computer Science Sichuan University

Object detection is an important task in drone vision. Since the number of objects and their scales always vary greatly in the drone-captured video, small object-oriented feature becomes the bottleneck of model performance, and most existing object detectors tend to underperform in drone-vision scenes. To solve these problems, we propose a novel detector named YOLO-Drone. In the proposed detector, the backbone of YOLO is firstly replaced with ConvNeXt, which is the state-of-the-art one to extract more discriminative features. Then, a novel scale-aware attention(SAA) module is designed in detection head to solve the large disparity scale problem. A scale-sensitive loss(SSL) is also introduced to put more emphasis on object scale to enhance the discriminative ability of the proposed detector. Experimental results on the latest VisDrone 2022 test-challenge dataset(detection track) show that our detector can achieve average precision(AP) of 39.43%, which is tied with the previous state-of-the-art, meanwhile,reducing 39.8% of the computational cost.

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6DOF pose estimation of a 3D rigid object based on edge-enhanced point pair features

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Computational Visual Media 2024年第1期10卷 61-77页

作者： Chenyi Liu Fei Chen Lu Deng Renjiao Yi Lintao Zheng Chenyang Zhu Jia Wang Kai Xu College of Computing National University of Defense TechnologyChangsha410073China Department of Spine Surgery the Second Xiangya HospitalCentral South UniversityChangsha410011China Clinical Nursing teaching and research section the Second Xiangya HospitalChangsha410011China College of Meteorology and Oceanography National University of Defense TechnologyChangsha410073China Beijing Institute of Tracking and Communication Technology Beijing100094China

The point pair feature(PPF)is widely used for 6D pose estimation.In this paper,we propose an efficient 6D pose estimation method based on the PPF framework.We introduce a well-targeted down-sampling strategy that focuses on edge areas for efficient feature extraction for complex geometry.A pose hypothesis validation approach is proposed to resolve ambiguity due to symmetry by calculating the edge matching degree.We perform evaluations on two challenging datasets and one real-world collected dataset,demonstrating the superiority of our method for pose estimation for geometrically complex,occluded,symmetrical objects.We further validate our method by applying it to simulated punctures.

关键词： point pair feature(PPF) pose estimation object recognition 3D point cloud

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重症监护室智慧化管理措施减少临床虚假警报效果的整合性综述

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International Journal of Nursing Sciences 2024年第1期11卷 133-142页

作者：李冰玉岳丽青聂慧宇曹紫薇柴小桠彭彬张恬鸽黄伟红 teaching and research section of Clinical Nursing Xiangya Hospital of Central South UniversityChangshaHunanChina Xiangya School of Nursing Central South UniversityChangshaHunanChina “Mobile Health”Ministry of Education-China Mobile Joint Laboratory Xiangya Hospital of Central South UniversityChangshaHunanChina

目的医疗设备的频繁虚假警报可能导致护土警报疲劳,这可能导致反应行动延迟或错过警报,增加患者不良事件的风险。本综述旨在探讨重症监护室临床警报智慧化管理措施对减少临床虚假警报的应用效果。方法根据Whitmore 和Knaf的方法学框架,... 详细信息

目的医疗设备的频繁虚假警报可能导致护土警报疲劳,这可能导致反应行动延迟或错过警报,增加患者不良事件的风险。本综述旨在探讨重症监护室临床警报智慧化管理措施对减少临床虚假警报的应用效果。方法根据Whitmore 和Knaf的方法学框架,对6个数据库进行系统检索: PubMed, EMBASE,CINAHL,OVID,CochraneLibrary,Scopus,检索从每个数据库建库到2022年12月以英文或中文发表的临床警报的智慧化管理相关文章。采用乔安娜布里格斯研究所的评价工具(JBI-MAStARI)评估研究的质量,并对文献进行数据提取和分析。该研究已在PROSPERO完成注册(CRD42023411552)。结果共纳入7项研究。不同的警报智慧化管理措施有利于减少虚假警报数量和警报的持续时间,缩短护士对重要警报的应答时间,减轻护士的警报疲劳程度。在实践中,应用新的警报管理方式后取得了积极的效果。结论智慧化管理措施可能是警报减少的有效途径,医院迫切需要进行临床警报的智慧化管理。为确保更有效的患者监测、减少警报给护士带来的困扰,未来需要更多与人工智能相结合的警报管理手段,以实现关键警报的准确识别,确保护士对警报准确响应,并真正改善警报频繁的临床医疗环境。

关键词：人工智能临床警报重症监护室护士生理监测安全管理

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Multiple types of disease-associated RNAs identification for disease prognosis and therapy using heterogeneous graph learning

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Science China(Information Sciences) 2024年

作者： Wenxiang ZHANG Hang WEI Wenjing ZHANG Hao WU Bin LIU School of computer Science and Technology Beijing Institute of Technology School of computer Science and Technology Xidian University Department of teaching and research Shenzhen University General Hospital Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging National-Regional Key Technology Engineering Laboratory for Medical UltrasoundSchool of Biomedical Engineering Shenzhen University Medical School Advanced research Institute of Multidisciplinary Science Beijing Institute of Technology

Identifying disease-associated RNAs is crucial in revealing the pathogenic mechanisms of diseases[1], and biologists have made notable progress in this field[2]. However, more effective computational methods are needed to provide reference disease-associated RNAs, reducing the manpower and material resources required for biological experiments.

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Dose-response effect of pre-exercise carbohydrates under muscle glycogen unavailability:Insights from McArdle disease

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Journal of Sport and Health Science 2024年第3期13卷 398-408页

作者： Pedro L.Valenzuela Alfredo Santalla Lidia B.Alejo Andrea Merlo Asuncion Bustos Laura Castellote-Belles Roser Ferrer-Costa Nicola A.Maffiuletti David Barranco-Gil Tomas Pinos Alejandro Lucia Physical Activity and Health research Group(“PaHerg”) Research Institute of Hospital“12 de Octubre”(“imas12”)Madrid 28041Spain Department of Systems Biology University of AlcalaMadrid 28871Spain Department of Sport and computer Science Section of Physical Education and SportsFaculty of SportUniversidad Pablo de OlavideSevilla 41013Spain EVOPRED research Group Universidad Europea de CanariasTenerife 38300Spain Faculty of Sport Sciences Universidad Europea de MadridMadrid 28670Spain Gait&Motion Analysis Laboratory Sol et Salus HospitalTorre Pedrera di Rimini(RN)47922Italy Department of Clinical Biochemistry Laboratoris ClınicsHospital Universitari Vall d’HebronBarcelona 08035Spain Human Performance Lab Schulthess ClinicZurich 8008Switzerland Biomedical research Networking Center on Rare Disorders(CIBERER) Barcelona 08035Spain Mitochondrial and Neuromuscular Disorders Unit Vall d’Hebron Institut de RecercaUniversitat Autonoma de BarcelonaBarcelona 08035Spain

Background:This study aimed to determine the effect of different carbohydrate(CHO)doses on exercise capacity in patients with McArdle disease—the paradigm of“exercise intolerance”,characterized by complete muscle glycogen unavailability—and to determine whether higher exogenous glucose levels affect metabolic responses at the McArdle muscle cell(in vitro)level.Methods:Patients with McArdle disease(n=8)and healthy controls(n=9)underwent a 12-min submaximal cycling constant-load bout followed by a maximal ramp test 15 min after ingesting a non-caloric placebo.In a randomized,double-blinded,cross-over design,patients repeated the tests after consuming either 75 g or 150 g of CHO(glucose:fructose=2:1).Cardiorespiratory,biochemical,perceptual,and electromyographic(EMG)variables were assessed.Additionally,glucose uptake and lactate appearance were studied in vitro in wild-type and McArdle mouse myotubes cultured with increasing glucose concentrations(0.35,1.00,4.50,and 10.00 g/L).Results:Compared with controls,patients showed the“classical”second-wind phenomenon(after prior disproportionate tachycardia,myalgia,and excess electromyographic activity during submaximal exercise,all p<0.05)and an impaired endurance exercise capacity(-51%ventilatory threshold and55%peak power output,both p<0.001).Regardless of the CHO dose(p<0.05 for both doses compared with the placebo),CHO intake increased blood glucose and lactate levels,decreased fat oxidation rates,and attenuated the second wind in the patients.However,only the higher dose increased ventilatory threshold(+27%,p=0.010)and peak power output(+18%,p=0.007).In vitro analyses revealed no differences in lactate levels across glucose concentrations in wild-type myotubes,whereas a doseresponse effect was observed in McArdle myotubes.Conclusion:CHO intake exerts beneficial effects on exercise capacity in McArdle disease,a condition associated with total muscle glycogen unavailability.Some of these benefits are dose dependent.

关键词： Endurance Glycogen storage disease Glycogenosis Nutrition Supplement

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护士参与抗菌药物管理现状及影响因素研究（英文）

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International Journal of Nursing Sciences 2024年第1期 91-98+159-160页

作者：聂慧宇岳丽青彭欢周金平李冰玉曹紫薇 1.teaching and research section of Clinical Nursing, Xiangya Hospital of Central South University 2.Xiangya School of Nursing, Central South University teaching and research section of Clinical Nursing Xiangya Hospital of Central South University Xiangya School of Nursing Central South University

目的基于能力、机会、动机和行为(capability,opportunity,motivation,and behavior,COM-B)理论,调查我国护十抗菌药物管理(antmicroD1al stewardship,AMS)参与水平及其影响因素,为制订有效策略提高AMS护理质量提供参考依据。方法采... 详细信息

目的基于能力、机会、动机和行为(capability,opportunity,motivation,and behavior,COM-B)理论,调查我国护十抗菌药物管理(antmicroD1al stewardship,AMS)参与水平及其影响因素,为制订有效策略提高AMS护理质量提供参考依据。方法采用横断面调查法。于2021年11月至2022年1月,选取湖南省的17所三级医院的4 514名护士进行调查。在COM-B理论指导下,自行编制护士参与抗菌药物管理问卷(the Nurse AMS Engagement Questionnaire,NAEQ)。该问卷包括能力(14个条目)、机会(7个条目)、动机(6个条目)和行为(12个条目)4个维度,共39个条目。结果护十NAEQ总分为(155.08±27.12)分,得分率为79.5%,表明护士参与AMS处于中等水平。其中,能力维度得分为(52.33±13.48)分,机会维度得分为(28.64±5.76)分,动机维度得分为(24.57±4.57)分,行为维度得分为(49.53±8.83)分。不同职称、是否兼职感染控制护士、是否知晓AMS团队、是否知晓抗菌药物限定口剂量、科室类型、科室是否配备临床药师、参与抗菌药物培训和医师-护士联合查房的频率等特征不同的护士NAEQ得分比较,差异有统计学意义(P<0.05)。其中初级职称护士的NAEQ得分高于中级职称护士(P<0.05);担任兼职感染控制护士、知晓AMS团队、知晓抗菌药物限定日剂量的护士NAEQ得分高于其他护上(P<0.01);重症监护室和传染病科护士NAEQ得分低于五官科等其他科室的护士(P<0.01);科室配备临床药师的护士NAEQ得分高于未配备或不清楚是否配备临床药师的护士(P<0.01);参与抗菌药物培训和医师-护十联合查房次数较多的护士NAEQ得分高于其他护十(P<0.01)。结论加强教育和培训及改善多学科沟通与协作等多种策略有望提高护士参与AMS的水平。此外,应更多关注中级职称、感染控制经验较少以及特定科室工作的护士。

关键词：抗菌药物管理行为中国医院知识动机护士

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From non-scattering to super-scattering with Mie-tronics

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Photonics research 2024年第4期12卷 608-624页

作者： HOOMAN BARATI SEDEH NATALIA M.LITCHINITSER Department of Electrical and computer Engineering Duke UniversityDurhamNorth Carolina 27708USA

Electric anapoles, arising from the destructive interference of primitive and toroidal electric dipole moments, have recently emerged as a fundamental class of non-scattering sources. On the other hand, super-scattering states represent the opposite regime wherein the scattering cross-section of a subwavelength particle exceeds the single-channel limit, leading to a strong scattering behavior. Here, we demonstrate that the interplay between the topology of light and the subwavelength scatterer can lead to these two opposite responses within an isolated alldielectric meta-atom. In particular, we present the emergence of a new non-scattering state, referred to as hybrid anapole, which surpasses conventional electric dipole anapoles by achieving a remarkable 23-fold enhancement in the suppression of far-field radiation and almost threefold enhancement in the confinement of electromagnetic energy inside the meta-atom. We also explore the role of particle orientation and its inversion symmetry in the scattering response and predict the possibility of switching between non-scattering and super-scattering states within the same platform. The presented study elucidates the role of light and matter topologies in the scattering response of subwavelength meta-atoms, uncovering two opposite regimes of light-matter interaction and opening new avenues in applications such as nonlinear optics and spectroscopy.

关键词： spectroscopy opposite dipole

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YOLO-MFD:Remote Sensing Image Object Detection with Multi-Scale Fusion Dynamic Head

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computers, Materials & Continua 2024年第5期79卷 2547-2563页

作者： Zhongyuan Zhang Wenqiu Zhu School of computer Science Hunan University of TechnologyZhuzhou412007China

Remote sensing imagery,due to its high altitude,presents inherent challenges characterized by multiple scales,limited target areas,and intricate backgrounds.These inherent traits often lead to increased miss and false detection rates when applying object recognition algorithms tailored for remote sensing imagery.Additionally,these complexities contribute to inaccuracies in target localization and hinder precise target categorization.This paper addresses these challenges by proposing a solution:The YOLO-MFD model(YOLO-MFD:Remote Sensing Image Object Detection withMulti-scale Fusion Dynamic Head).Before presenting our method,we delve into the prevalent issues faced in remote sensing imagery analysis.Specifically,we emphasize the struggles of existing object recognition algorithms in comprehensively capturing critical image features amidst varying scales and complex backgrounds.To resolve these issues,we introduce a novel approach.First,we propose the implementation of a lightweight multi-scale module called CEF.This module significantly improves the model’s ability to comprehensively capture important image features by merging multi-scale feature information.It effectively addresses the issues of missed detection and mistaken alarms that are common in remote sensing imagery.Second,an additional layer of small target detection heads is added,and a residual link is established with the higher-level feature extraction module in the backbone section.This allows the model to incorporate shallower information,significantly improving the accuracy of target localization in remotely sensed images.Finally,a dynamic head attentionmechanism is introduced.This allows themodel to exhibit greater flexibility and accuracy in recognizing shapes and targets of different sizes.Consequently,the precision of object detection is significantly improved.The trial results show that the YOLO-MFD model shows improvements of 6.3%,3.5%,and 2.5%over the original YOLOv8 model in Precision,map@0.5 and map@0.5:0.95,separately.These results illustr

关键词： Object detection YOLOv8 multi-scale attention mechanism dynamic detection head

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