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京东健康旗下AI工具“京东知医”全面升级: 聚焦循证医学与临床工作流

亿邦动力 2026-04-30 11:24
亿邦动力 2026/04/30 11:24

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京东健康升级AI工具“京东知医”,提升临床工作效率。

1.功能增强:支持拍照、图片、PDF等多种格式上传,能解析检验报告、处方等临床资料,并生成AI分析结果;新增个性化订阅推送,医生可定制最新诊疗指南和医学资讯。

2.安全保障:搭建全流程安全防护体系,包括数据合规审核和智能预警;针对高风险场景如用药方案强化交叉核对机制;专家委员会设计“Medscope”四维评测体系,覆盖46个临床科室,确保输出准确性。

3.应用实例:AI医生“大为”服务用户超千万,好评率达98%以上;工具集成至京东医生App,免费供医生使用,提升日常病例分析和患者管理效率。

京东健康通过AI创新强化品牌影响力,聚焦产品研发和用户行为洞察。

1.产品研发:升级“京医千询”医疗大模型,优化AI生成逻辑,扩充临床语料库,提升专业性和准确性;开发全场景AI应用体系,包括面向C端用户的AI医生“大为”、营养师“小晶”等智能体,覆盖多健康场景。

2.消费趋势:AI工具如“知医”支持个性化推送,反映用户对知识更新的需求;AI医生服务累计超千万用户,好评率高,显示用户对AI医疗的接受度提升。

3.品牌渠道:工具免费开放,集成于京东医生App,增强医生用户粘性;代表企业京东健康依托“AI+供应链”优势,如“京东卓医”解决方案落地医院,拓展品牌渠道建设。

AI医疗工具提供增长市场和合作机会,需关注风险提示。

1.增长市场:AI在医疗中加速落地,如“京东知医”支持患者管理和循证分析,系统结合问诊、处方等数据提供个体化建议;AI医生“大为”覆盖慢病管理,显示消费需求变化。

2.合作方式:京东健康与多家医院合作落地“京东卓医”解决方案,聚焦临床营养等场景;平台提供免费工具如“知医”,可视为扶持政策,促进医生合作。

3.风险提示:安全体系应对高风险场景如用药禁忌,强化多证据核对;模型幻觉率保持低水平,但需注意医疗AI潜在风险;最新商业模式如专家智能体帮助医生预约门诊,提供可学习点。

AI工具启示数字化推进和商业机会,助力产品设计。

1.数字化启示:升级工具支持多模态处理如解析药盒和皮肤影像,启示工厂在数字化生产中整合AI技术;循证分析功能可应用于产品研发,提升设计效率。

2.商业机会:京东健康“AI+供应链”优势在“京东卓医”中形成闭环,如提供特医食品供给,工厂可探索供应链合作;药智模型基于亿级用户数据,提供用药指导,启示工厂开发智能健康产品。

3.产品需求:工具新增动态证据定位功能,自动标注依据原文,可能启发工厂在产品设计中增强可追溯性;个性化推送反映用户定制化趋势,影响产品研发方向。

医疗AI行业趋势和技术解决方案突出客户痛点应对。

1.行业趋势:医疗大模型加速落地,AI智能体成为竞争关键;京东健康形成全场景AI应用体系,包括五大智能体群,覆盖用户、医生、医院等。

2.新技术:迭代“京医千询”大模型,优化生成逻辑和语料库;支持多模态输入和解析功能,提升临床适配能力。

3.解决方案:针对客户痛点如文献查阅效率低,“知医”工具直接输出结构化循证结论;安全体系解决高风险场景,如MedSafety评测覆盖26类情境;专家智能体帮助医生承接咨询,提供自动化服务方案。

平台集成AI工具提升运营管理,需规避风向。

1.平台做法:京东健康将“知医”集成至京东医生App,免费开放;平台推出“AI京医”体系,上线超1500个专家医生智能体,覆盖皮肤、中医等专科,帮助招商拓展。

2.运营管理:搭建全流程安全防护体系,包括数据审核和智能预警,强化高风险场景交叉核对;日常注重专业性与实用性平衡,提升平台稳定性。

3.风向规避:安全评测体系如Medscope降低模型幻觉风险;平台提供个性化订阅功能,医生可定制内容,规避信息过载风险;合作医院落地解决方案,如“京东卓医”聚焦实际场景,减少运营风险。

产业新动向和商业模式创新,提供政策启示。

1.产业动向:医疗大模型迭代加速,如“京医千询”优化生成逻辑;AI工具“知医”新增多模态功能,提升临床工作流适配;全场景AI应用体系形成五大智能体群,显示AI在医疗中深化。

2.商业模式:矩阵包括面向C端用户的AI医生群、专家数字分身群、医生工具群、医院解决方案群和药智模型群;药智模型基于亿级数据,提供病前介入、用药守护等主动服务,从被动转向主动陪伴。

3.政策启示:专家委员会设计四维循证评测体系Medscope,覆盖证据质量和实用性;安全体系如MedSafety针对禁忌用药等高风险情境,建议政策强化AI医疗规范;案例显示模型幻觉率低,启示监管框架设计。

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Quick Summary

JD Health has upgraded its AI tool "JD Zhiyi" to enhance clinical workflow efficiency.

1. Enhanced functionality: Supports uploading various formats like photos, images, and PDFs; can parse clinical data such as lab reports and prescriptions to generate AI analysis results; adds personalized subscription push notifications, allowing doctors to customize the latest treatment guidelines and medical information.

2. Security assurance: Established a full-process security protection system, including data compliance reviews and intelligent alerts; strengthened cross-verification mechanisms for high-risk scenarios like medication plans; an expert committee designed the "Medscope" four-dimensional evaluation system covering 46 clinical departments to ensure output accuracy.

3. Application examples: AI doctor "Dawei" has served over 10 million users with a satisfaction rate exceeding 98%; the tool is integrated into the JD Doctor App and offered free to doctors, improving daily case analysis and patient management efficiency.

JD Health strengthens brand influence through AI innovation, focusing on product development and user behavior insights.

1. Product development: Upgraded the "Jingyi Qianxun" medical large language model, optimized AI generation logic, and expanded the clinical corpus to enhance professionalism and accuracy; developed a full-scenario AI application system, including AI doctor "Dawei" and nutritionist "Xiaojing" for C-end users, covering multiple health scenarios.

2. Consumer trends: AI tools like "Zhiyi" support personalized push notifications, reflecting user demand for knowledge updates; the AI doctor service has cumulatively served over 10 million users with high satisfaction, indicating growing user acceptance of AI in healthcare.

3. Brand channels: Free tools integrated into the JD Doctor App enhance doctor user stickiness; JD Health leverages its "AI + Supply Chain" advantage, such as deploying the "JD Zhuoyi" solution in hospitals, to expand brand channel development.

AI medical tools present growth markets and partnership opportunities, requiring attention to risk alerts.

1. Growth market: AI is accelerating its adoption in healthcare; tools like "JD Zhiyi" support patient management and evidence-based analysis, integrating consultation and prescription data to provide personalized recommendations; AI doctor "Dawei" covers chronic disease management, reflecting evolving consumer demands.

2. Partnership models: JD Health collaborates with multiple hospitals to implement the "JD Zhuoyi" solution, focusing on scenarios like clinical nutrition; the platform offers free tools like "Zhiyi" as supportive policies to foster doctor cooperation.

3. Risk alerts: The security system addresses high-risk scenarios like medication contraindications with enhanced multi-evidence verification; model hallucination rates remain low, but potential risks of medical AI require caution; emerging business models, such as expert AI agents assisting doctors with appointment scheduling, offer learnable insights.

AI tools offer insights into digital advancement and business opportunities, aiding product design.

1. Digital insights: Upgraded tools support multimodal processing, such as parsing medication boxes and skin images, suggesting factories integrate AI technology into digital production; evidence-based analysis functions can be applied to product R&D to improve design efficiency.

2. Business opportunities: JD Health's "AI + Supply Chain" advantage creates closed-loop systems in "JD Zhuoyi," such as supplying special medical foods, offering factories potential supply chain collaborations; the drug intelligence model, based on billions of user data points, provides medication guidance, inspiring factories to develop smart health products.

3. Product demand: New features like dynamic evidence positioning with automatic source annotation may inspire factories to enhance traceability in product design; personalized push notifications reflect user customization trends, influencing R&D directions.

Medical AI industry trends and technical solutions address key customer pain points.

1. Industry trends: Medical large language models are accelerating deployment, with AI agents becoming a competitive differentiator; JD Health has established a full-scenario AI application system comprising five major AI agent groups, covering users, doctors, and hospitals.

2. New technology: Iterated the "Jingyi Qianxun" large language model, optimizing generation logic and the corpus; supports multimodal input and parsing functions, enhancing clinical adaptability.

3. Solutions: Addresses customer pain points like inefficient literature review—"Zhiyi" directly outputs structured evidence-based conclusions; the security system tackles high-risk scenarios, with MedSafety evaluations covering 26 scenarios; expert AI agents help doctors handle consultations, providing automated service solutions.

Platform integration of AI tools enhances operational management while requiring risk mitigation.

1. Platform strategy: JD Health integrates "Zhiyi" into the JD Doctor App, offering it for free; the platform launched the "AI Jingyi" system, deploying over 1,500 expert doctor AI agents covering specialties like dermatology and traditional Chinese medicine to aid merchant acquisition and expansion.

2. Operational management: Established a full-process security protection system, including data reviews and intelligent alerts, with strengthened cross-verification for high-risk scenarios; daily operations balance professionalism and practicality to improve platform stability.

3. Risk mitigation: Evaluation systems like Medscope reduce model hallucination risks; personalized subscription features allow doctors to customize content, mitigating information overload risks; partnerships with hospitals to implement solutions like "JD Zhuoyi" focus on practical scenarios, reducing operational risks.

Industry developments and business model innovations offer policy insights.

1. Industry动向: Medical large language models are iterating rapidly, such as "Jingyi Qianxun" optimizing generation logic; AI tool "Zhiyi" adds multimodal functions, improving clinical workflow integration; the formation of a full-scenario AI application system with five major AI agent groups indicates deepening AI integration in healthcare.

2. Business models: The matrix includes AI doctor groups for C-end users, expert digital twin groups, doctor tool groups, hospital solution groups, and drug intelligence model groups; the drug intelligence model, based on billions of data points, provides proactive services like pre-illness intervention and medication guardianship, shifting from passive to active companionship.

3. Policy启示: The expert committee designed the four-dimensional evidence-based evaluation system Medscope, covering evidence quality and practicality; security systems like MedSafety address high-risk situations like contraindicated medications, suggesting policies strengthen AI medical regulations; cases show low model hallucination rates, informing regulatory framework design.

Disclaimer: The "Quick Summary" content is entirely generated by AI. Please exercise discretion when interpreting the information. For issues or corrections, please email run@ebrun.com .

I am a Brand Seller Factory Service Provider Marketplace Seller Researcher Read it again.

【亿邦原创】日前,京东健康股份有限公司(简称“京东健康”)宣布,其面向临床医生推出的循证医学AI工具“京东知医”已完成全面升级。目前,该工具的能力已集成至“京东医生”App中,供医生用户免费使用。

据京东健康介绍,此次升级主要围绕循证能力强化、医疗安全保障体系搭建及临床实用功能扩展三个方向展开,旨在通过AI技术辅助医生提升文献查阅、病例分析、患者管理等日常工作的效率。

01“京医千询”医疗大模型迭代 提升回答的专业性与准确性

在底层技术层面,京东健康对自研的“京医千询”医疗大模型进行了迭代,通过优化AI生成逻辑、扩充优质临床语料库及多版本模型对比训练,提升回答的专业性与准确性。

同时,京东健康搭建了从数据合规审核到高风险场景智能预警的全流程安全防护体系,以降低医疗AI应用的潜在风险。针对疑难会诊、用药方案等高风险场景,系统强化了多证据交叉核对机制;在日常诊疗、文献解读等高频场景,则注重专业性与实用性的平衡。

京东健康成立了专家委员会,为“京东知医”设计了名为“Medscope”的四维循证评测体系,从证据质量、内容准确性、表达规范性和整体实用性四个维度对AI输出进行校验。评测集覆盖46个主要临床科室。此外,专门设立的“MedSafety”安全评测体系覆盖了禁忌用药、并发症预警等26类高风险医疗情境。

京东健康表示,该工具已完成对全球权威医学数据库的动态更新,涵盖最新版诊疗指南、国际期刊研究成果及官方药品说明书。京东健康方面称,在多维度内部评测中,“京东知医”的模型幻觉率持续保持较低水平。

02“京东知医”新增多模态处理与个性化推送功能 提升了工具对临床工作流的适配能力

据悉,“京东知医”于2026年1月上线,是京东健康在医疗AI领域的重要产品之一。此次升级是其上线后的首次大规模迭代。

在功能层面,本轮升级重点提升了工具对临床工作流的适配能力。新版本支持拍照、图片、PDF等多种格式的资料上传,能够解析检验报告、处方、化验单、药盒及皮肤影像等临床资料,并生成AI分析结果。

同时,“动态证据定位”功能可自动标注AI建议所依据的原文语句,以增强结论的可追溯性。在患者管理方面,该工具可接入平台积累的患者病历数据,医生可直接对自己管理或线下录入的患者资料进行循证分析,系统会结合患者的历史问诊、处方、病历及医生备注等信息,提供个体化建议。

此外,“京东知医”新增了个性化订阅推送功能。医生可以根据自身的执业科室和研究方向,订阅最新的诊疗指南和前沿医学资讯,以便进行知识更新。

03依托京医千询大模型 ,京东健康形成了面向用户、医生、医院、药企的全场景AI应用体系

当前,随着医疗大模型加速落地,AI智能体已成为医疗健康服务格局竞争的关键变量。京东健康依托自研“京医千询”大模型技术底座,形成了面向用户、医生、医院、药企的全场景AI应用体系。矩阵从横向拓展能力边界、纵向深化专业深度两个方向不断演化,目前已形成四大核心智能体群。

第一群:面向C端用户的专业服务智能体。 涵盖多种健康服务角色。其中,AI医生“大为”作为矩阵的核心代表角色,专门为用户提供从常见病咨询到慢病日常管理的解决方案。据京东健康的数据,2025年至今,AI医生“大为”好评率已达98%以上,累计服务用户超千万。在“大为”之外,矩阵中还包括AI营养师“小晶”、AI药师“小方”、AI护士、AI健康管家等十多类专业服务智能体,覆盖多个健康场景。

第二群:专家医生智能体——医生本人的“数字分身”。 京东健康将全国各大三甲医院专家的专业知识、临床经验、思维模式和表达习惯深度数字化,训练出医生的专属AI分身。截至2026年1月,京东健康“AI京医”体系已上线超1500个来自全国各地三甲医院的专家医生智能体,覆盖皮肤、精神心理、中医等多个重点专科-。这些专家智能体帮助医生承接日常工作中大量的基础咨询,以及可以为进一步诊疗的患者自动预约门诊时间。

第三群:面向医生的AI赋能工具“知医”。 在服务患者之外,京东健康智能体矩阵也包含面向医生的智能体。2026年1月,京东健康发布了专为临床医生研发的循证医学AI产品“知医”,旨在帮助医生在诊疗和科研中快速筛选、整合海量前沿信息,直接输出结构化、可落地的循证结论。“知医”现已全面集成于京东医生APP中,面向全体医生免费开放使用。

第四群:面向医院的“京东卓医”全场景解决方案。 在机构服务层面,京东健康推出了业内首个医院全场景大模型产品“京东卓医”,已在温医大附一院、中日友好医院等多家医院落地。据悉,(JD Healthcare)其2.0版本深度融合京东健康独特的“AI+供应链”优势,聚焦临床营养、院外用药、体重代谢等实际场景,形成“AI建议+专业服务+高品质特医食品和健康品供给”的全链路闭环。

第五群:面向全产业链的“药智模型”矩阵。京东健康方面介绍,“药智模型”基于4000万权威知识源、200万医疗实体及亿级用户行为数据训练而成。该模型旨在让AI在病发前介入、用药时守护、康复后陪伴。京东健康指出,基于药智模型,AI药师能够提供7X24小时在线服务,购药之前,它能将用户模糊的“不舒服”诉求转化为清晰的用药方案;购药过程中,它能提为用户提供供个性化的合理用药指导与风险评估;用户购药之后,它还会主动提醒复购、复诊,帮助慢性病用户延长规范用药周期。从被动的应答者到主动的陪伴者。

亿邦持续追踪报道该情报,如想了解更多与本文相关信息,请扫码关注作者微信。

文章来源:亿邦动力

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