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孕期体重增长对0~3岁儿童生长轨迹的影响

卫生研究 2024年第3期53卷 375-381页

作者：杨雅涵叶梓李俊王杰中国疾病预防控制中心营养与健康所中国疾病预防控制中心母乳科学研究重点实验室国家卫生健康委公共营养与健康重点实验室北京100050 太仓市妇幼保健计划生育服务中心苏州215413

目的分析0~3岁儿童年龄别体质指数Z评分(body mass index for age Z score,BAZ)的轨迹,并探讨孕期体重增长水平与儿童BAZ轨迹的关联。方法基于前瞻性队列研究,于2013年至2017年在江苏太仓地区招募孕早期孕妇作为研究对象,追踪其孕期体... 详细信息

目的分析0~3岁儿童年龄别体质指数Z评分(body mass index for age Z score,BAZ)的轨迹,并探讨孕期体重增长水平与儿童BAZ轨迹的关联。方法基于前瞻性队列研究,于2013年至2017年在江苏太仓地区招募孕早期孕妇作为研究对象,追踪其孕期体重变化,采用中国标准计算和评价孕期体重增长(孕期体重增长适宜、不足或过多)。测量儿童出生、1、3、6、8、12、18、24、30和36月龄时的身高/身长和体重,并计算各年龄的BAZ分值。采用基于组的轨迹模型拟合儿童BAZ轨迹。运用多水平Logistic回归分析孕期体重增长水平与BAZ轨迹之间的关联,并调整相关影响因素对结果的影响。结果1864对母婴数据被纳入分析,其中0~3岁儿童的BAZ可拟合为3组轨迹:生长较缓组(34.07%)、生长适宜组(48.23%)和生长快速组(17.70%)。单因素分析显示,以孕期体重增长适宜的母亲为对照组,孕期体重增长不足会增加子代生长较缓的风险(OR=1.95,95%CI 1.28~2.96),孕期体重增长过多可增加子代生长快速的风险(OR=1.57,95%CI 1.19~2.07);多因素分析中调整了母亲孕前体质指数、产次、儿童性别及出生体重后,孕期体重增长不足的母亲其子代生长较缓的风险更高(OR=1.84,95%CI 1.19~2.84);而孕期体重增长过多与儿童早期生长轨迹间关联无统计学意义(OR=1.26,95%CI 0.94~1.68)。结论0~3岁儿童BAZ轨迹可分为生长较缓组、生长适宜组及生长快速组;母亲孕期体重增长不足可增加0~3岁儿童生长较缓的风险。

关键词：生长轨迹孕期体重增长婴幼儿 BAZ评分

The critical need to establish standards for data quality in intelligent medicine

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Intelligent Medicine 2021年第2期1卷 49-50页

作者： Ruiyang Li yahan yang Haotian Lin State Key Laboratory of Ophthalmology Zhongshan Ophthalmic CentreSun Yat-sen UniversityGuangzhouGuangdong 510623China Centre for Precision Medicine Sun Yat-sen UniversityGuangzhouGuangdong 510080China

Medical artificial intelligence(AI)is an important technical asset to support medical supply-side reforms and national development in the big data era.Clinical data from multiple disciplines represent building blocks for the development and application of AI-aided diagnostic and treatment systems based on medical big data.However,the inconsistent quality of these data resources in AI research leads to waste and inefficiencies.Therefore,it is crucial that the field formulatesthe requirements and content related to data processing as part of the development of intelligent medicine.To promote medical AI research worldwide,the“Belt and Road”International Ophthalmic Artificial Intelligence Research and Development Alliance will establish a series of expert recommendations for data quality in intelligent medicine.

关键词： Artificial intelligence Intelligent medicine Big data Data collection Data storage Data management

黄河流域县域乡村空心化地域类型及乡村振兴路径

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地理科学进展 2024年第6期43卷 1049-1059页

作者：付占辉杨雅涵乔家君朱肖勇江孝君河南大学地理与环境学院河南开封475004 黄河中下游数字地理技术教育部重点实验室河南开封475004 河南大学国际商学院郑州470000 唐山师范学院资源管理系河北唐山063000

“人”是乡村生产发展的主体,从人口演变视角揭示黄河流域乡村空心化的地域类型及其驱动机制,对推进黄河流域生态保护、乡村振兴发展具有重要的意义。论文利用人口普查资料和XGBoost模型,分析黄河流域县域乡村空心化的地域类型、时空差... 详细信息

“人”是乡村生产发展的主体,从人口演变视角揭示黄河流域乡村空心化的地域类型及其驱动机制,对推进黄河流域生态保护、乡村振兴发展具有重要的意义。论文利用人口普查资料和XGBoost模型,分析黄河流域县域乡村空心化的地域类型、时空差异及其形成机制,提出不同地区乡村振兴路径。研究发现:(1)黄河流域乡村空心化可划分为空废型、衰败型、衰退型、衰弱型、增长型等5种地域类型,其中,衰败型增长幅度最大,由2000—2010年的16%增长到2010—2020年的39%;衰弱型的降幅最大,由29%下降到12%。黄河流域上游、中游和下游乡村空心化地域类型正向变化最大的为中游的衰败型(增幅为43个百分点),负向变化最大的为下游的衰弱型(降幅为34个百分点)。(2)乡村空心化地域类型的时空差异显著,且空间集聚特征逐渐显现,增长型和衰弱型空间分布范围不断萎缩,衰败型空间分布呈扩张态势,衰弱型和衰败型逐渐向黄河上游集聚。(3)从黄河流域整体看,不同阶段乡村空心化地域类型空间分异的主导因素不同,但县域城镇化、地形等因素一直发挥了较大的作用。上游地区受县域城镇化的影响一直较大,对中游地区影响较大的因素由2000—2010年的县域城镇化演变为2010—2020年的农业现代化,县域城镇化、地形对下游地区的作用更大。(4)黄河流域上、中、下游地区自然环境、人文经济的空间差异大,乡村空心化地域类型的流域差异显著,各地区乡村振兴路径务必要结合地方特色,创新发展模式,加快形成城乡融合、工农互促的良性格局,推动乡村振兴发展。研究结果可为黄河流域农业农村现代化发展提供科学决策依据。

关键词：人口演变乡村空心化地域类型 XGBoost模型乡村振兴黄河流域

Expert recommendations on data collection and annotation of two dimensional ultrasound images in azoospermic males for evaluation of testicular spermatogenic function in intelligent medicine

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Intelligent Medicine 2022年第2期2卷 97-102页

作者： Wanling Huang Yifan Xiang yahan yang Qing Tang Guangjian Liu Hong yang Erjiao Xu Huitong Lin Zhixing Zhang Zhe Ma Zhendong Li Ruiyang Li Anqi Yan Haotian Lin Zhu Wang Chinese Association of Artificial Intelligence Medical Artificial Intelligence Branch of the Guangdong Medical Association Department of Medical Ultrasonics Institute of Diagnostic and Interventional UltrasoundFirst Affiliated Hospital of Sun Yat-Sen UniversityGuangzhouGuangdong 510080China State Key Laboratory of Ophthalmology Zhongshan Ophthalmic CenterSun Yat-Sen UniversityGuangzhouGuangdong 510080China Department of Medical Ultrasound First Affiliated Hospital of Guangzhou Medical UniversityGuangzhouGuangdong 510120China Department of Medical Ultrasonics Sixth Affiliated HospitalSun Yat-Sen UniversityShenzhen 510665China Department of Medical Ultrasound First Affiliated Hospital of Guangxi Medical UniversityNanningGuangxi Zhuang Autonomous Region530021China Department of Medical Ultrasonics Eighth Affiliated HospitalSun Yat-Sen UniversityShenzhen 518033China Department of Medical Ultrasonics Seventh Affiliated HospitalSun Yat-Sen UniversityShenzhen 518107China NHC Key Laboratory of Male Reproduction and Genetics Guangdong Provincial Reproductive Science InstituteGuangdong Provincial Fertility HospitalGuangzhouGuangdong 510600China Department of Medical Ultrasonics First Affiliated Hospital of Shandong First Medical UniversityShandong Provincial Qianfoshan HospitalJinanShandong 250014China Department of Medical Ultrasonics Lanzhou University Second HospitalLanzhouGansu 730030China Zhongshan School of Medicine Sun Yat-Sen UniversityGuangzhouGuangdong 510080China 不详

Testicular two-dimensional ultrasound is a testing modality that is often used to evaluate azoospermia and other related diseases.With the continuous development of deep learning in recent years,the combination of deep learning and testicular ultrasound appears unstoppable despite a lack of relevant standards.One of the major problems associated with the digitization of ultrasound images is the uneven quality of data however,and a standardized data source and acquisition process has not yet been developed.Such a standard could fill the current gap,and establish acquisition criteria for ultrasound images of testes during the male reproductive period,including grayscale ultrasound,shear wave elastography,and contrast-enhanced ultrasound.By following these guidelines the quality of testicular ultrasound images would be improved and standardized,which would lay a solid foundation for the standardization of testicular ultrasound images,and assist automated evaluation of testicular spermatogenic function of whole testis in azoospermic males.

关键词： Ultrasound Azoopsermia Testicular spermatogenic function

Expert recommendations on collection and annotation of otoscopy images for intelligent medicine

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Intelligent Medicine 2022年第4期2卷 230-234页

作者： Yuexin Cai Junbo Zeng Liping Lan Suijun Chen Yongkang Ou Linqi Zeng Qintai yang Peng Li Yubin Chen Qi Li Hongzheng Zhang Fan Shu Guoping Chen Wenben Chen yahan yang Ruiyang Li Anqi Yan Haotian Lin Yiqing Zheng Department of Otolaryngology Sun Yat-sen Memorial HospitalSun Yat-sen UniversityGuangzhouGuangdong 510120China Shenshan Medical Center Sun Yat-sen Memorial HospitalSun Yat-sen UniversityShanweiGuangdong 516600Chin Zhongshan Ophthalmic Center Sun Yat-sen UniversityState Key Laboratory of OphthalmologyGuangzhouGuangdong 510623China Zhongshan School of Medicine Sun Yat-sen UniversityGuangzhouGuangdong 510080China Department of Otolaryngology Head and Neck Surgery The Third Affiliated Hospital of Sun Yat-sen UniversityGuangzhouGuangdong 510630China Department of Otolaryngology-Head and Neck Surgery Nanfang HospitalSouth Medical UniversityGuangzhouGuangdong 510515China Department of Otolaryngology-Head&Neck Surgery Zhujiang HospitalSouth Medical UniversityGuangzhouGuangdong 510280China Department of Otolaryngology Zhongshan City People’s HospitalZhongshan Affiliated Hospital of Sun Yat-sen UniversityZhongshanGuangdong 528403China

Middle and outer ear diseases are common otological diseases worldwide.Otoscopy and otoendoscopy exami-nations are essential first steps in the evaluation of patients with otological diseases.Misdiagnosis often occurs when the doctor lacks experience in interpreting the results of otoscopy or otoendoscopy,leading to delays in treatment or complications.Using deep learning to process otoscopy images and developing otoscopic artificial-intelligence-based decision-making systems will become a significant trend in the future.However,the uneven quality of otoscopy images is among the major obstacles to development of such artificial intelligence systems,and no standardized process for data acquisition,and annotation of otoscopy images in intelligent medicine has yet been fully established.The standards for data storage and data management are unified with those of other specialties and are introduced in detail here.This expert recommendation criterion improved and standardized the collection and annotation procedures for otoscopy images and fills the current gap in otologic intelligent medicine;it would thus lay a solid foundation for the standardized collection,storage,and annotation of oto-scopy images and the application of training algorithms,and promote the development of automatic diagnosis and treatment for otological diseases.The full text introduced image collection(including patient preparation,equipment standards,and image storage),image annotation standards,and quality control.

关键词： Otoscopy image Intelligent medicine Annotation Collection

Recommendation on data collection and annotation of ocular appearance images in ptosis

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Intelligent Medicine 2023年第4期3卷 287-292页

作者： Jie Meng Binying Lin Dongmei Li Shiqi Hui Xuanwei Liang Xianchai Lin Zhen Mao Xingyi Li Zuohong Li Rongxin Chen yahan yang Ruiyang Li Anqi Yan Haotian Lin Danping Huang Chinese Association of Artificial Intelligence,Medical Artificial IntelligenceBranch of Guangdong Medical Association Zhongshan Ophthalmic Center Sun Yat-sen UniversityState Key Laboratory of OphthalmologyGuangzhouGuangdong 510080China Beijing Tongren Eye Center Beijing Key Laboratory of Intraocular Tumor Diagnosis and TreatmentBeijing Ophthalmology&Visual Sciences Key LabMedicalArtificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information TechnologyBeijing Tongren HospitalCapital MedicalUniversityBeijing 100730China Zhongshan School of Medicine Sun Yat-sen UniversityGuangzhouGuangdong 510080China

Ptosis is a common ophthalmologic condition,and the diagnosis is primarily based on ocular appearance.Thediagnosis of such conditions can be improved using emerging technology such as artificial intelligence-basedmethods.However,unified data collection and labeling standards have not yet been established.This directlyimpacts the accuracy of ptosis diagnosis based on appearance alone.Therefore,in the present study,we aimedto establish a procedure to obtain and label images to devise a recommendation system for optimal recognitionof ptosis based on ocular appearances.This would help to standardize and facilitate data sharing and serve as aguideline for the development and improvisation of algorithms in artificial intelligence for ptosis.

关键词： Ptosis Ocular appearance image Annotation standard Artificial intelligence

Expert recommendation on collection,storage,annotation,and management of data related to medical artificial intelligence

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智慧医学(英文) 2023年第2期3卷 144-149页

作者： yahan yang Ruiyang Li Yifan Xiang Duoru Lin Anqi Yan Wenben Chen Zhongwen Li Weiyi Lai Xiaohang Wu Cheng Wan Wei Bai Xiucheng Huang Qiang Li Wenrui Deng Xiyang Liu Yucong Lin Pisong Yan Haotian Lin Chinese Association of Artificial Intelligence Medical Artificial Intelligence Branch of Guangdong Medical Association Zhongshan Ophthalmic Center Sun Yat-sen UniversityState Key Laboratory of OphthalmologyGuangzhouGuangdong 510623China Zhongshan School of Medicine Sun Yat-sen UniversityGuangzhouGuangdong 510080China Nanjing University of Aeronautics and Astronautics NanjingJiangsu 210016China Institute of Software Engineering School of Computer Science and TechnologyXidian UniversityXi’anShaanxi 710071China Cloud Intelligent Care Tech.Ltd. GuangzhouGuangdong 510115China Centre for Precision Medicine Sun Yat-sen UniversityGuangzhouGuangdong 510080China 不详

Medical artificial intelligence(AI)and big data technology have rapidly advanced in recent years,and they are now routinely used for image-based diagnosis.China has a massive amount of medical data.However,a uniform criteria for medical data quality have yet to be established.Therefore,this review aimed to develop a standardized and detailed set of quality criteria for medical data collection,storage,annotation,and management related to medical AI.This would greatly improve the process of medical data resource sharing and the use of AI in clinical medicine.

关键词： Artificial intelligence Big data Intelligent medicine Data collection Data storage Data annotation Data management

Highly Stable Nonhydroxyl Antisolvent Polymer Dielectric:A New Strategy towards High-Performance Low-Temperature Solution-Processed Ultraflexible Organic Transistors for Skin-Inspired Electronics

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Research 2021年第1期2021卷 1615-1626页

作者： Mingxin Zhang Cong Zhang yahan yang Hang Ren Junmo Zhang Xiaoli Zhao Yanhong Tong Qingxin Tang Yichun Liu Centre for Advanced Optoelectronic Functional Materials Research and Key Laboratory of UV-Emitting Materials and Technology Ministry of EducationNortheast Normal UniversityChangchun 130024China

Scarcity of the antisolvent polymer dielectrics and their poor stability have significantly prevented solution-processed ultraflexible organic transistors from low-temperature,large-scale production for applications in low-cost skin-inspired electronics.Here,we present a novel low-temperature solution-processed PEI-EP polymer dielectric with dramatically enhanced thermal stability,humidity stability,and frequency stability compared with the conventional PVA/c-PVA and c-PVP dielectrics,by incorporating polyethyleneimine PEI as crosslinking sites in nonhydroxyl epoxy EP.The PEI-EP dielectric requires a very low process temperature as low as 70℃ and simultaneously possesses the high initial decomposition temperature(340℃)and glass transition temperature(230℃),humidity-resistant dielectric properties,and frequency-independent capacitance.Integrated into the solution-processed C8-BTBT thin-film transistors,the PEI-EP dielectric enables the device stable operation in air within 2 months and in high-humidity environment from 20 to 100%without significant performance degradation.The PEI-EP dielectric transistor array also presents weak hysteresis transfer characteristics,excellent electrical performance with 100%operation rate,high mobility up to 7.98 cm^(2)V^(-1)s^(-1)(1 Hz)and average mobility as high as 5.3 cm^(2)V^(-1)s^(-1)(1 Hz),excellent flexibility with the normal operation at the bending radius down to 0.003 mm,and foldable and crumpling-resistant capability.These results reveal the great potential of PEI-EP polymer as dielectric of low-temperature solution-processed ultraflexible organic transistors and open a new strategy for the development and applications of next-generation low-cost skin electronics.

关键词： dielectric humidity stability

An Improved Non-coupled PCNN Model for Image Segmentation

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An Improved Non-coupled PCNN Model for Image Segmentation