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梅滑
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1 让互联网 + 医疗的每次进步都成为确定的幸福 The progress of Internet Plus Healthcare promotes the happiness of people 周旋腾讯互联网 + 医疗高级产品总监 Xuan Zhou Tencent Internet Plus Healthcare Department, Senior Product Director

2 什么是互联网 +? What is "Internet plus"? 互联网 + 是手段, 数字经济是结果, 网络强国是目的 "Internet plus" is the means, the digital economy is the result, the network power is the purpose. 民政医疗交通人社公安教育 Civil affairs Medical Traffic MOHRSS Police Education 连接 Connect 赋能 Energize Interconnection Intelligence Service Ecology

3 什么是互联网 + 医疗? What is "Internet Plus Healthcare? 以互联网技术和解决方案, 助力医疗行业发展 Internet technology and solutions will promote the development of medical industry. 腾讯医疗生态 3.8 亿用户 1.1 亿月活病变病变家药店 2000 家医院赋能医院生态微信开放能力微信公众号微信企业号微信支付互联网 + 可以做什么? 在已有的医疗生态体系内 : 完善医疗领域需要的基础能力整合腾讯多年积累的技术能力提供生态需要的标准解决方案促成更健康的医疗生态 What can Internet Plus do? In the existing medical ecosystem: To improve the basic capacities needed in the medical field. To integrate Tencent's technical capacities accumulated over the years. To provide standard solutions for ecosystem. To promote a healthier medical ecosystem

4 Case 1 连接 Connect 微信医疗支付 Medical payment via Wechat 2 赋能 Energize 腾讯觅影 Tencent MIAIS

5 通过互联网技术的连接, 为民众带来确定的幸福 The connection of Internet technology promotes the happiness of people. 1 微信医疗支付 Medical payment via Wechat 1 医保支付 Medical insurance payment 2 新农合支付 NCMS payment 3 商保支付 Commercial insurance payment

6 1 医保支付 Medical insurance payment 连接人社医院和患者, 为患者就医缴费平均节省 43.6 分钟 WeChat connects MOHRSS, hospitals and patients, saving 43.6 minutes on average for patients.

7 2 新农合支付 NCMS payment 连接卫计委医院和患者, 为农村患者就医减少资金垫付和异地奔波 WeChat connects NHFPC, hospitals and patients, reducing the financial pressure for rural patients.

8 3 商保支付 Commercial insurance payment 连接保险公司医院和患者, 让患者就医商保报销更便捷 WeChat connects insurance companies, hospitals and patients, making it easier for patients to apply for reimbursement. 刘筠璨

9 通过互联网技术的赋能, 为民众带来确定的幸福 The energization of Internet technology promotes the happiness of people. 2 腾讯觅影 Tencent MIAIS 1 技术储备 Technical reserves 2 解决痛点 Solutions 3 未来计划 Future plans

10 1 腾讯公司的人工智能技术积累 Tencent AI technology 腾讯近十年一直在积累并使用图像识别等人工智能技术 Tencent has been developing artificial intelligence technology for nearly a decade. 图像识别 image recognition 深度学习 Deep Learning 应用案例 Case 硬件投入 Hardware 海量的图片库与极强的图片处理能腾讯 AI Lab 研发的围棋 AI 绝艺, 福建公安厅运用腾讯优图天眼寻人引大规模的 GPU 计算集群, 价值数亿力用户日发送照片达到 15 亿 / 日在日本举办的第 10 届 UEC 杯计算机擎, 搭建了牵挂你防走失平台深度网络可缩短到 1 天训练完, 单围棋大赛中, 获得冠军成功找回 171 起走失案例个病历 (50 张图片 )6s 可处理完

11 1 人工智能 + 医学影像腾讯觅影 AI + Medical imaging MIAIS 腾讯财报 : 人工智能具有战略意义, 我们会持续进行长期投资 Tencent finicial report: artificial intelligence is significant for our strategy and we will continue to invest for the long term.

12 2 腾讯觅影 : 解决痛点 MIAIS : To solve the pain points 据了解, 卫计委人社医生患者均有痛点 According to the surveys, NHFPC, MOHRSS, doctors and patients have pain points. 早期治疗治愈率超过 90% 术后 3-5 天出院并发症少治疗费用元左右进展期 / 晚期治愈率不足 40% 术后恢复时间长, 生活质量下降治疗费用 12 万左右

2 腾讯觅影 : 技术原理 MIAIS : Technology principle

Multi-Instance Learning Using the method of

Multi-Instance Learning 算法思想 Ranked prob.

图像 patch 集合 (c) Patch 的癌症概率估计 (d) 最大 patch

13 2 腾讯觅影 : 技术原理 MIAIS : Technology principle 借鉴计算机视觉目标跟踪 (Tracking) 领域的方法 :Deep Multi-Instance Learning Using the method of object tracking in computer vision: Deep Multi-Instance Learning 算法思想 Ranked prob. f( ) = probability p( ) = max{ } (a) 原始图像 (b) 图像 patch 集合 (c) Patch 的癌症概率估计 (d) 最大 patch 的标签作为图像标签模型训练 CNN Linear Regression Ranked prob. f( ) = probability Loss Functions 13

14 2 腾讯觅影 : 跨界合作 MIAIS : Cross-field cooperation 需要医生的专业指导和紧密配合 MIAIS needs professional guidance and close collaboration from doctors.

15 2 腾讯觅影 : 效果验证 MIAIS : Effect verification 腾讯觅影考试成绩 : 食管癌早癌识别率 90% The result of MIAIS: Early esophageal cancer recognition rate reaches 90%.

16 3 腾讯觅影 : 短期目标 MIAIS : Short-term goals 早期食管癌筛查早期肺癌筛查糖尿病视网膜病变筛查 Early esophageal cancer screening Early lung cancer screening Diabetic retinopathy screening 宫颈癌筛查乳腺癌筛查乳腺癌淋巴清扫切片筛查 Cervical cancer screening Breast cancer screening Breast cancer screening by lymph node biopsy

17 3 腾讯觅影 : 长期目标 MIAIS : Long-term goals 科研基层公益 Scientific research Grass-roots Public service

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