地理信息系统在血吸虫病研究中的应用

地理信息系统（GIS）是集计算机科学、地理学、测绘学、空间科学、信息科学等为一体的新兴科争[1],并已逐渐应用于卫生管理决策和疾病监测中[15]。GIS结合遥感技术也将是血吸虫病防治研究的实用工具之一[2,3,4]。因此,本文针对血吸虫病流行特征,就GIS及相关技术,如遥感、全球定位系统等技术应用于血吸虫病防治工作的范围、前景作一综述。1GIS概述1．1GIS基本概念及应用范围GIS是地理信息学方法的一种实现手段,是多学科集成并应用于各领域的基础平台[1]。Aronoff将GIS定义为“任何用于贮存和处理与地理位置有关的数据信息的人…     

血吸虫病防控技术集成研究与示范 Ⅱ疫情纵向防治效果评价

目的评价血吸虫病防控技术集成研究与示范对控制血吸虫病疫情的防治效果。方法通过在示范区实施封洲轮牧、改水改厕、健康教育等控制血吸虫病流行的综合措施,并开展血吸虫病疫情调查及相关问卷调查,评价其防治效果。结果通过连续3年的血吸虫病防控技术实施,示范区居民血吸虫感染率由3.57%降至0.83%,耕牛血吸虫感染率由17.14%降至0,洲滩未发现阳性钉螺。结论封洲轮牧、改水改厕、健康教育等综合防治技术是控制鄱阳湖区血吸虫病流行的有效措施。     

我国家畜血吸虫病流行情况及防控进展

本文介绍了我国家畜血吸虫病造成的危害及在血吸虫病传播中的作用；回顾了我国家畜血吸虫病的防控历程，及不同防控时期家畜血吸虫病流行情况；指出虽然我国家畜血吸虫病疫情已得到有效控制，但影响血吸虫病流行与传播的多种因素依然存在，该病在局部地区仍有死灰复燃或疫情回升的风险。血防工作者需继续加强疫情监测和重点地区防治力度，巩固防控成果，突破消除家畜血吸虫病的关键技术难点，探讨提出精准防控技术措施和策略，推进我国消除血吸虫病进程。     

重视羊血吸虫病防治 推进我国消除血吸虫病进程

虽然我国血吸虫病防治工作已取得举世瞩目的成就,但日本血吸虫病仍是我国重要的公共卫生问题之一。日本血吸虫可自然感染四十余种哺乳动物。自2004年以来,我国实施了以传染源控制为主的血吸虫病综合防治策略,并将牛作为重点防控对象,重点实施了家畜圈养、封洲禁牧、以机代牛、安全牧场以及对感染牛化疗等控制措施,取得了显著成效,流行区人和牛血吸虫感染率以及感染性钉螺面积均已降至历史最低水平,全国血吸虫病防治进程正由传播控制向传播阻断乃至消除迈进。羊是血吸虫易感动物之一,既往流行病学资料显示部分流行区羊血吸虫感染率较高。但羊作为日本血吸虫病主要传染源在疾病传播过程中的作用尚未得到足够重视,且目前尚缺乏有关羊在我国日本血吸虫病传播中作用的专项调查和系统研究。江苏省血吸虫病防治研究所梁幼生研究员课题组通过实验室研究和现场调查,对羊在日本血吸虫病传播中的作用进行了系统研究。课题组对日本血吸虫在山羊体内的发育与繁殖（产卵）、羊粪对环境的污染、温度和湿度对羊粪中血吸虫虫卵存活的影响等进行了观察和调查,进一步明确了羊在日本血吸虫病传播中的作用,并结合既往研究成果,提出羊是我国日本血吸虫病重要传染源之一,有必要将羊日本血吸虫病综合治理纳入国家层面的防控规划。课题组还对羊血吸虫感染粪便孵化技术进行了改进,优化了羊血吸虫病病原诊断技术。这些创新性研究工作填补了国内在羊日本血吸虫病研究领域的一些空白,研究成果将丰富我国以传染源控制为主的血吸虫病综合防治策略,在我国消除血吸虫病进程中发挥应有的作用。鉴于血吸虫病流行会严重影响流行区养羊业发展和当地农民收入,且羊已经成为部分流行区血吸虫病传播重要的传染源之一,做好羊血吸虫病防控工作有助于推进我国消除血吸虫病进程。建议重点做好以下两方面工作：① 重视羊血吸虫病防控工作,将羊血吸虫病综合治理纳入国家层面的防控规划; ② 研发适用于羊血吸虫病防控的技术、产品和措施。     

安徽省血吸虫病发现、流行及防治简史

安徽曾是我国血吸虫病流行最为严重的省份之一。 本文探讨了安徽省血吸虫病的发现历史, 描述了新中国成立前血吸虫病带来的严重危害;概括了新中国成立后全省血吸虫病的防控历程和取得的显 著成效;重点归纳了长期实践中安徽省血吸虫病防控所作的探索和创新,尤其在血吸虫病诊断技术、防控策 略以及兴林抑螺等方面做了大量开创性工作,为全省乃至全国的血吸虫病控制工作作出了突出贡献,发挥 了举足轻重的作用。     

凝练中国血吸虫病防控成功经验 贡献于WHO指南在全球实施

血吸虫病是一种严重阻碍社会经济发展、威胁公共卫生安全的寄生虫病。为实现2030年全球消除作为一种公共卫生问题的血吸虫病,2022年2月WHO发布了《WHO控制和消除人体血吸虫病指南》,旨在为各国实现控制血吸虫病发病率、将其作为一种公共卫生问题消除及最终达到传播阻断提供循证建议。在历史上血吸虫病曾经严重流行的中国,经过有效防控策略和措施的实施,血吸虫病防控工作取得了重大成绩,逐步迈向消除血吸虫病。本文回顾中国血吸虫病防控策略、防控关键技术和实践的成功经验,贡献于《WHO控制和消除人体血吸虫病指南》的制定与实施。随着“一带一路”倡议的深入推进,世界也期待更多血吸虫病防控领域的“中国方案”。     

"一带一路"倡议下血吸虫病防控南南合作的战略思考

经过近70年的积极努力,我国血吸虫病防控工作取得了巨大成就。当前,我国血吸虫病防控工作一方面要解决向消除血吸虫病进程迈进中的“最后一公里”问题;同时要为全球血吸虫病消除工作贡献“中国经验”、“中国方案”和“中国智慧”,以推动共建“一带一路”倡议向高质量发展转变,为全球卫生安全服务。本文分析了全球血吸虫病流行现状及防控工作面临的挑战,阐述了“一带一路”沿线国家血吸虫病防控合作的基础,剖析了我国血吸虫病防控经验与技术输出面临的挑战,并提出了“一带一路”倡议下血吸虫病防控南南合作方式与发展前景。     

血吸虫病诊断技术研究进展

［摘要］　血吸虫病是一种重要的人兽共患寄生虫病，被WHO归类为被忽视的热带病。经过70年的努力，我国血吸虫病防控工作取得了巨大成就，血吸虫感染率和致残致死率显著下降。近年来，随着“一带一路”倡议、中非合作深入推进，输入性血吸虫病病例时有报告，输入性血吸虫病在中国大陆的潜在传播风险值得关注。为了更好地巩固血吸虫病防控成果、提升对外部生物安全风险的检测能力，本文对血吸虫病病原学、免疫学与核酸等诊断技术研究进展进行综述。     

组分抗原在血吸虫病免疫诊断中的研究进展

血吸虫病一直危害着人类的健康,尤其在我国,血吸虫病的防治仍是公共卫生事业的一项重要任务.血吸虫病特异性诊断抗原的研制一直是本领域研究的热点,随着分子生物技术的迅速发展,有关血吸虫病的诊断抗原已由原始的粗抗原发展为重组抗原、组分抗原等.该文就虫卵、成虫、尾蚴等组分抗原在血吸虫病诊断中的研究作一综述.     

洪涝灾害与血吸虫病防控

当前,我国血吸虫病疫情处于历史最低水平,但影响血吸虫病传播与流行的因素依然存在。洪涝灾害对血吸虫病流行会产生严重影响,甚至影响血吸虫病防治进程和防治成果的巩固。2020年,我国较大范围发生了严重洪涝灾害。本文分析了当前我国血吸虫病流行现状及洪涝灾害对血吸虫病流行的影响,并就洪涝灾害发生前的风险评估与处置、发生时的感染风险防范以及灾后疫情评估与监测等血吸虫病防控工作进行了系统阐述。洪涝灾害地区的血吸虫病防控既是常规防治工作的重要部分,又是救灾防病工作的重要环节,应在各地政府的统一领导下科学有序地实施各项应急响应措施,避免或减少洪涝灾害所致血吸虫病传播风险;同时要重视和加强血吸虫病早期监测预警技术和方法研究,为实现《 “十三五”全国血吸虫病防治规划》和全面消除血吸虫病目标提供科学精准的支撑。     

人工智能在消化内镜中的临床应用现状

随着人工智能（artificial intelligence,AI）技术的不断发展,以大数据为支撑兼具强大计算能力和学习能力的AI技术已用于解决复杂的医学问题。利用AI分析大量非结构化医学数据,并执行临床任务,开始出现在胃肠镜检查中。即使与专业的内镜医师相比,AI技术也能够表现出优异的灵敏度和准确率,计算机辅助检查和计算机辅助诊断技术有望改变传统的内镜检查模式。本文就AI技术在消化系统内镜中的应用进行探讨。     

人工智能技术在结直肠癌中的应用与展望

人工智能技术自问世以来,一直被人们不断研究,并取得飞跃式的发展。目前,人工智能技术已在科研、经济和日常生活等方面得到广泛运用。在医学方面,人工智能主要应用在许多疾病的诊断、治疗和预后预测中。结直肠癌是常见的一种消化道恶性肿瘤,其早期的诊断和治疗是影响其预后的关键因素。本文将综述人工智能在结直肠癌诊治中的应用现状,并展望人工智能在结直肠癌中更加深入和广泛运用的前景。     

Health Technology Assessment for Cardiovascular Digital Health Technologies and Artificial Intelligence: Why Is It Different?

Innovations in health care are growing exponentially, resulting in improved quality of and access to care, as well as rising societal costs of care and variable reimbursement. In recent years, digital health technologies and artificial intelligence have become of increasing interest in cardiovascular medicine owing to their unique ability to empower patients and to use increasing quantities of data for moving toward personalised and precision medicine. Health technology assessment agencies evaluate the money spent on a health care intervention or technology to attain a given clinical impact and make recommendations for reimbursement considerations. However, there is a scarcity of economic evaluations of cardiovascular digital health technologies and artificial intelligence. The current health technology assessment framework is not equipped to address the unique, dynamic, and unpredictable value considerations of these technologies and highlight the need to better approach the digital health technologies and artificial intelligence health technology assessment process. In this review, we compare digital health technologies and artificial intelligence with traditional health care technologies, review existing health technology assessment frameworks, and discuss challenges and opportunities related to cardiovascular digital health technologies and artificial intelligence health technology assessment. Specifically, we argue that health technology assessments for digital health technologies and artificial intelligence applications must allow for a much shorter device life cycle, given the rapid and even potentially continuously iterative nature of this technology, and thus an evidence base that maybe less mature, compared with traditional health technologies and interventions.     

人工智能助力热带传染病防控研究

自新型冠状病毒肺炎疫情发生以来,人工智能技术在热带传染病领域应用的先进性逐渐凸显。人工智能技术的应用对缓解疾病诊疗负担、降低疾病漏诊和误诊率、提升疾病监测预警能力、提高医药和疫苗研发效率等均具有显著成效。本文分析了人工智能在热带传染病防控研究中的应用现状,论述了人工智能在该领域疾病诊疗、监测预警、疫苗与药物挖掘、医疗与公共卫生服务和全球卫生治理中的重要价值。根据人工智能助力热带传染病防控面临着诊断单一和不准确、开放环境监测预警能力不佳、智能系统服务能力有限、大数据管理困难、模型可解释性较差等方面的难题,本文提出了加强多种热带传染病多模态智能诊断、重视开放环境下媒介生物和风险人群智能监测预警、加快智能防控系统研发、强化伦理安全、大数据管理与模型可解释性等发展建议。     

Artificial intelligence in gastrointestinal endoscopy:The future is almost here

Artificial intelligence(AI) enables machines to provide unparalleled value in a myriad of industries and applications. In recent years, researchers have harnessed artificial intelligence to analyze large-volume, unstructured medical data and perform clinical tasks, such as the identification of diabetic retinopathy or the diagnosis of cutaneous malignancies. Applications of artificial intelligence techniques, specifically machine learning and more recently deep learning, are beginning to emerge in gastrointestinal endoscopy. The most promising of these efforts have been in computeraided detection and computer-aided diagnosis of colorectal polyps, with recent systems demonstrating high sensitivity and accuracy even when compared to expert human endoscopists. AI has also been utilized to identify gastrointestinal bleeding, to detect areas of inflammation, and even to diagnose certain gastrointestinal infections. Future work in the field should concentrate on creating seamless integration of AI systems with current endoscopy platforms and electronic medical records, developing training modules to teach clinicians how to use AI tools, and determining the best means for regulation and approval of new AI technology.     

眼科开展医学人工智能研究的学科优势

视觉障碍严重威胁人类健康和生活质量,亟需新型的智能诊疗模式以满足巨大的防盲治盲需求。眼科开展医学人工智能研究具有明显的学科优势,包括眼睛是多脏器健康状况的观察窗口、眼科疾病具有较高的临床安全性和应用可推广性等。眼科医学人工智能研究的模式,可为其他领域的医学人工智能临床研究和应用模式探索提供重要参考作用。     

人工智能在消化系肿瘤的研究进展

伴随着人工智能技术在医疗领域的迅猛发展，强大的计算和深度学习能力已引起了全球医疗领域人士的共同关注。尤其是近年来，人工智能在消化系统肿瘤方面的应用取得了显著的发展，为临床医师诊治消化系肿瘤提供了一种全新的"心理-社会-生物医学-人工智能"的诊疗新模式，也为患有消化系肿瘤的患者带来新的精准诊治方案。本文对人工智能在消化系肿瘤的研究进展进行如下综述。     

Artificial intelligence in Hematology

Artificial intelligence (AI) is a computer based science which aims to simulate human brain faculties using a computational system. A brief history of this new science goes from the creation of the first artificial neuron in 1943 to the first artificial neural network application to genetic algorithms.

The potential for a similar technology in medicine has immediately been identified by scientists and researchers. The possibility to store and process all medical knowledge has made this technology very attractive to assist or even surpass clinicians in reaching a diagnosis.

Applications of AI in medicine include devices applied to clinical diagnosis in neurology and cardiopulmonary diseases, as well as the use of expert or knowledge-based systems in routine clinical use for diagnosis, therapeutic management and for prognostic evaluation. Biological applications include genome sequencing or DNA gene expression microarrays, modeling gene networks, analysis and clustering of gene expression data, pattern recognition in DNA and proteins, protein structure prediction.

In the field of hematology the first devices based on AI have been applied to the routine laboratory data management. New tools concern the differential diagnosis in specific diseases such as anemias, thalassemias and leukemias, based on neural networks trained with data from peripheral blood analysis. A revolution in cancer diagnosis, including the diagnosis of hematological malignancies, has been the introduction of the first microarray based and bioinformatic approach for molecular diagnosis: a systematic approach based on the monitoring of simultaneous expression of thousands of genes using DNA microarray, independently of previous biological knowledge, analysed using AI devices. Using gene profiling, the traditional diagnostic pathways move from clinical to molecular based diagnostic systems.     

Artificial intelligence in hematology

Artificial intelligence (AI) is a computer based science which aims to simulate human brain faculties using a computational system. A brief history of this new science goes from the creation of the first artificial neuron in 1943 to the first artificial neural network application to genetic algorithms. The potential for a similar technology in medicine has immediately been identified by scientists and researchers. The possibility to store and process all medical knowledge has made this technology very attractive to assist or even surpass clinicians in reaching a diagnosis. Applications of AI in medicine include devices applied to clinical diagnosis in neurology and cardiopulmonary diseases, as well as the use of expert or knowledge-based systems in routine clinical use for diagnosis, therapeutic management and for prognostic evaluation. Biological applications include genome sequencing or DNA gene expression microarrays, modeling gene networks, analysis and clustering of gene expression data, pattern recognition in DNA and proteins, protein structure prediction. In the field of hematology the first devices based on AI have been applied to the routine laboratory data management. New tools concern the differential diagnosis in specific diseases such as anemias, thalassemias and leukemias, based on neural networks trained with data from peripheral blood analysis. A revolution in cancer diagnosis, including the diagnosis of hematological malignancies, has been the introduction of the first microarray based and bioinformatic approach for molecular diagnosis: a systematic approach based on the monitoring of simultaneous expression of thousands of genes using DNA microarray, independently of previous biological knowledge, analysed using AI devices. Using gene profiling, the traditional diagnostic pathways move from clinical to molecular based diagnostic systems.     

血吸虫病网络地理信息系统软件开发及应用

目的利用网络地理信息系统（WebGIS） 技术开发江苏省血吸虫病网络地理信息系统.方法在江苏省血吸虫病地理信息系统（GIS）数据库的基础上,利用ESRI公司的ArcIMS软件开发主动式江苏省血吸虫病WebGIS.结果江苏省血吸虫病WebGIS已初步开发完成,并在江苏省血吸虫病防治研究所内部局域网试运行,实现了江苏省血吸虫病管理控制中相关的各类地理数据、属性数据、专业库、资料库数据的统一管理,提供各种查询、显示、分析、统计以及图形输出等功能.结论利用WebGIS技术开发血吸虫病GIS是可行的,为建立江苏省血吸虫病管理决策系统提供了基础.