Releasing of The White Paper on Medical Imaging Artificial Intelligence in China

In the afternoon of March 26,2019, The White Paper on Medical Imaging Artificial Intelligence in China was officially released in Beijing by the Chinese Innovative Alliance of Industry, Education, Research and Application of Artificial Intelligence for Medical Imaging (CAIERA). The white paper was co-operatively written by the medical imaging experts from the tertiary Chinese hospitals, the scientific experts from AI research institutions and the leading AI medical enterprises in China. The contents of the white paper not only cover the up-to-date application of AI in medical field, the latest advances of AI algorithms in medical image processing, the data requirement for medical AI development, and the current situation of structured data, but also expatiate the goal and challenge of clinical application for medical imaging AI development in 16 medical subject areas, which helps to identify the demands and opportunities for the AI industry. Forty representative enterprises of AI medical imaging in China were introduced in the white paper. The white paper points out the three key problems in development of AI products: the robustness, ease of usage and data security, which provides guidance of direction and strategy for the enterprises. Particularly, in view of the national policy on developing AI, the white paper gives a profound analysis on the challenges and the opportunities that medical imaging AI is facing. These contents agglomerate the cutting-edge efforts of experts in the industry-academia-research-application chain of medical AI, represent the mainstream voice of the society in China. The White Paper will play a guiding role in understanding the market demands and establishing standardized systems in the path of landing AI products in the field medical imaging. Full text of the White paper is publicly accessible from the CAIERA website, or by scanning the 2D code in the article.     

人工智能医疗器械质量管理标准化趋势分析

目的旨在研究人工智能(Artificial Intelligence,AI)医疗器械质量管理的发展趋势,促进标准规范研究。方法根据AI医疗器械相关监管、法规的最新动态,梳理质量管理面临的特殊问题;结合产品检测实践情况,分析AI医疗器械质量管理的需求与发展方向。结果在AI医疗器械的质量管理过程中,可溯源性、数据集管理、质量控制等方面都需进一步增强。结论本文研究的思路和方法有助于建立适合AI医疗器械的专用标准规范。     

人工智能大模型在医疗领域的应用现状与前景展望

目的/意义 梳理分析人工智能大模型在医疗领域的应用现状,为人工智能大模型在该领域的研究提供新思路。方法/过程 在相关文献分析基础上,梳理人工智能大模型在智慧医疗、医疗元宇宙、医学研究等领域的应用场景及具体实例,总结人工智能大模型在医疗领域应用的风险与挑战。结果/结论 人工智能大模型在医疗领域具有广阔的发展空间,应推动人工智能大模型核心技术发展,进一步完善相关规范与法律。     

大系统人工智能的医学路线

大系统医学人工智能在中国的第一次兴起，是伴随着微型计算机引入中国，时间点在上世纪八十年代，技术特征是模仿诊疗过程，典型应用集中在中医界，杰出代表是朱文锋教授[1]。但发展至上世纪九十年代中后期，由于大系统医学人工智能是一门复杂的交叉学科，对人才的复合技能要求非常高，特别是数学建模技能对于一些医学科研工作来说很难，从而使得医学人工智能的发展较为缓慢，科凌力智能也不例外，但一直在坚持。今天，阿尔法围棋（AlphaGo）的面世，又激起了我们坚持下去的勇气。     

人工智能和虚拟现实技术在孤独症患者康复训练中的应用

在上世纪80年代,人们对孤独症的认识普遍不足,甚至把它归类为精神障碍。在近30多年的研究中,虽然其发病机制仍然未明,发病率却在逐年递增。孤独症临床表现各异,缺乏交流与互动,甚至生活不能自理,给家庭和社会带来了沉重的负担。目前治疗多以早期教育训练为主,但一对一的强化训练,在训练机构与专业人员水平参差不齐的今天,也不能满足患者的需求。寻求训练代理的想法,使研究人员发现了信息技术在孤独症训练领域的应用前景。全球在人工智能技术与虚拟技术应用于孤独症康复训练中的深入研宄,至今已经取得了可喜的成果。     

Collaborations of Industry,Academia, Research and Application Improve the Healthy Development of Medical Imaging Artificial Intelligence Industry in China

In recent years, artificial intelligence (AI) has developed rapidly in the field of medical imaging. However, the collaborations among hospitals, research institutes and enterprises are insufficient at the present, and there are various issues in technological transformation and value landing of products in this area. To solve the core problems in the developmental path of medical imaging AI, the Chinese Innovative Alliance of Industry, Education, Research and Application of Artificial Intelligence for Medical Imaging compiled the White Paper on Medical Image AI in China. This article introduces the current status of collaboration, the clinical demands for medical imaging AI technique, and the key points in AI technology transformation: robustness, usability and security. We are facing challenges of lacking industry standards, data desensitization standard, assessment system, as well as corresponding regulations and policies to realize the application values of AI products in medical imaging. Further development of AI in medical imaging requires breakthroughs of the core algorithm, deep involvement of doctors, input from capitals, patience from societies, and most importantly, the resolutions from government for multiple difficulties in links of landing the technology.     

人工智能在电子病案管理系统中的应用

目的:通过引用人工智能技术,解决电子病案管理系统中存在的缺陷。方法:采用文字识别、语音识别、生物识别、人脸识别等技术,对电子病案进行检索、整合、统计、分析。结果:通过人工智能技术在电子病案管理系统中的应用,大大提高了病案管理人员的工作效率,助力临床科研和教学。结论:人工智能技术的广泛应用,为医疗卫生信息化的发展带来质的飞跃,人们将不仅仅是借助信息化的力量提高工作效率,并且可以利用信息化的数据整合,为以后的发展发挥更大的作用。     

人工智能技术在眼科问诊中的探索与应用

目的:探索人工智能技术在眼科门诊问诊方面的应用.方法:本研究结合眼科专家共识和诊疗常规,建立思维导图,导入脱敏数据,训练人工神经网络模型,通过人机对话实现既往史、现病史、过敏史以及家族史的智能采集.临床实践采用人-机对照实验对系统进行验证.结果:29 367例患者中,干预组(人工智能组)患者3 850例,对照组(医生人...     

医学人工智能领域的技术创新态势研究

目的:通过对医学人工智能领域获得授权的发明专利分析,揭示全球技术竞争态势。方法:对医学人工智能领域近20年全球发明专利授权情况进行分析,从发明专利授权数量与趋势、技术发源地、目标市场、专利权机构、发明人、技术热点等角度展示该领域的技术创新趋势,揭示中国的技术实力水平。结果与结论:全球医学人工智能领域发明专利授权量逐年增长,技术热点聚焦于医学影像、药物研发、辅助诊断三个方向。中国成为继美国之后的全球第二大技术发源地和目标市场,中国多个专利权机构和发明人的发明专利授权量跻身全球前列。     

医疗人工智能产品对患者安全的影响及对策研究

构建医疗人工智能产品对患者安全影响框架,结合临床实践,从医疗人工智能研发者、医疗机构、卫生技术人员、政府4个角度分析医疗人工智能产品对患者安全的不利影响,提出相关对策建议,为完善患者安全保障体系提供参考依据.     

提高我院病案质量的管理体会

目的加强病案管理及病案书写质量监控,提高病案内涵质量。方法分析总结2008年1月-10月456份出院病案终末质量监控发现的问题,完善病案管理规章制度,建立病案质量三级检查体系和奖惩制度,评选优秀病案进行展览。结果病案质量有了明显提高,各级医师提高了病案书写规范的认识。结论病案管理是医院管理中一项非常细致的工作,提高病案质量需要各级领导的高度重视和互相配合,提高医务工作者的责任心和专业知识,增强法律意识,严格执行奖惩制度。     

医学人工智能与生态动力学问题（一）

从医学人工智能研究对象的特殊性入手，分析了经典决定论工具的成长局限和不适应原理，提出新的生态动力学理论结构和操作方法，并据此建立起新的医学人工智能模型。     

人工智能在临床基因组学中的应用进展

临床基因组学主要研究基因组信息在临床中的应用,包括诊断、治疗决策、预测预后。在传统的算法和技术难以处理基因组学中复杂又庞大的数据时,人工智能的应用带来新的希望。目前,人工智能已参与到临床基因组学的多种任务中,如识别变异、变异分类、影像-遗传诊断、电子病历-基因诊断、药物作用及不良反应预测等。本文主要综述临床基因组中不同方面的人工智能应用。     

Advances of Artificial Intelligence Application in Medical Imaging of Ovarian Cancers

Ovarian cancer is one of the three most common gynecological cancers in the world, and is regarded as a priority in terms of women's cancer. In the past few years, many researchers have attempted to develop and apply artificial intelligence (AI) techniques to multiple clinical scenarios of ovarian cancer, especially in the field of medical imaging. AI-assisted imaging studies have involved computer tomography (CT), ultrasonography (US), and magnetic resonance imaging (MRI). In this review, we perform a literature search on the published studies that using AI techniques in the medical care of ovarian cancer, and bring up the advances in terms of four clinical aspects, including medical diagnosis, pathological classification, targeted biopsy guidance, and prognosis prediction. Meanwhile, current status and existing issues of the researches on AI application in ovarian cancer are discussed.     

Innovative Applications of Patient Experience Big Data in Modern Hospital Management Improve Healthcare Quality

It is important for modern hospital management to strengthen medical humanistic care and build a harmonious doctor-patient relationship. Innovative applications of the big data resources of patient experience in modern hospital management facilitate hospital management to realize real-time supervision, dynamic management and scientific decision-making based on patients experiences. It is helping the transformation of hospital management from an administrator’s perspective to a patient’s perspective, and from experience-driven to data-driven. The technological innovations in hospital management based on patient experience data can assist the optimization and continuous improvement of healthcare quality, therefore help to increase patient satisfaction to the medical services.     

我国医学人工智能发展监管现状及政策建议

目的/意义 医学人工智能应用监管碎片化及数据的高门槛现状与医学人工智能发展需求之间矛盾日益突显。在各国积极部署数字健康战略的背景下,如何主动作为、为我国医学人工智能发展做好政策护航已成为亟待解决的问题。方法/过程 基于面向“产-学-研-用-管”多领域开展的调查研究及深度访谈资料,系统梳理医学人工智能特点及发展诉求,从国家战略和行业政策层面对当前监管体系现状进行分析。结果/结论 提出“构建医学人工智能监管衔接机制”的整体政策建议,从组织衔接、数据衔接、人才衔接和技术支撑4个角度展开,为破除当前发展壁垒、促进我国医学人工智能健康蓬勃发展提供解决思路。     

美国人工智能医疗器械监管与应用分析

近年来人工智能医疗器械发展迅速,美国在该类型器械的注册审批与监管制度建设上全球领先.本研究对美国食品药品监督管理局人工智能医疗器械监管制度和已上市产品的审批与应用情况进行分析,发现美国正在探索创新管理制度,希望通过对上市后真实世界数据的利用,加快产品上市速度、加强产品全生命周期监管.美国该领域发展虽仍处于起步阶段,但已...     

人工智能在国内外老年护理领域发展情况对比分析及启示

目的/意义分析人工智能在国内外老年护理领域的发展情况,提出完善人工智能在我国老年护理领域发展的启示和建议。方法/过程从政策保障、基础数据建设、技术发展、产品设计、人才培养5方面对比分析人工智能在国内外老年护理领域发展情况。结果/结论聚焦短板弱项加强制度体系建设、改进人工智能算法实现产品功能从供给侧转向需求侧、推动健康医疗数据结构化建设以加快数据共享、注重护理信息学人才培养与推动产学研结合等系列对策建议,将有助于推动人工智能在我国老年护理领域发展。     

完善牡丹江地区医院病人投诉处理机制研究

科学高效的病人投诉处理机制有利于管理者及时发现医院管理中存在的问题,进而提高医疗服务质量、更好地保障医疗服务安全。以牡丹江地区5所医院为样本,收集到926件病人投诉案例,通过调查研究和统计数据的分析,发现本地区医院在病人投诉处理工作中存在的问题。应研究并采用PDCA循环管理模式,建立和完善医院病人投诉处理机制。     

基于人工智能的病历质控系统的设计与应用

目的:探索有效提升病历质控效率和质量的方法.方法:通过质控规则拆解、质控引擎开发等,借助人工智能技术构建病历质控系统,应用于病历文书的环节质控和终末质控.结果:系统可实现病历的时效性、完整性等形式缺陷的筛查,实现对病历文书的术语规范性、数据一致性、逻辑一致性、诊断充分性、处置必要性等内涵缺陷质控,且系统具备数据集中展示...