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| 数智融合背景下重症医学科发展的机遇、挑战与对策 |
| 徐天宇1,2,余松轩2,侯冷晨2,马鸣骁2,何萍2,沈兵1,3* |
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(1. 上海理工大学健康科学与工程学院, 上海 200093;
2. 上海申康医院发展中心, 上海 200041;
3. 上海市第十人民医院, 上海 200072
*通信作者) |
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| 摘要: |
| 近年来，数字化与传统工业化深度融合的理论体系与实践路径逐渐成熟。医学创新和数字化技术顺应时代进程，重症医学科与智慧化的深度融合正打破传统信息化边界，迎来新的发展机遇。利用5G、大数据、人工智能、数字孪生等技术可帮助医护人员了解更为复杂的重症医学问题，提高疾病和症状的诊断及预测能力，制定更精准的治疗策略，甚至转变重症医学的服务模式。本文对数字化技术在重症医学实际场景中的应用和挑战进行归纳，为进一步夯实基础建设、丰富应用场景、加速应用落地、提升应用效果、强化安全合规提供建议与方向。 |
| 关键词: 数智融合 重症医学 人工智能 数字孪生 大数据 |
| DOI：10.16781/j.CN31-2187/R.20230753 |
| 投稿时间：2023-12-20修订日期：2024-02-23 |
| 基金项目:国家科技创新2030—“新一代人工智能”重大项目（2021ZD0113501）. |
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| Critical care medicine under the background of digital intelligence integration: opportunities, challenges, and strategies |
| XU Tianyu1,2,YU Songxuan2,HOU Lengchen2,MA Mingxiao2,HE Ping2,SHEN Bing1,3* |
(1. School of Health Science Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China;
2. Shanghai Hospital Development Center, Shanghai 200041, China;
3. Shanghai Tenth People's Hospital, Shanghai 200072, China
*Corresponding author) |
| Abstract: |
| Recently, the theoretical system and practical path for the deep integration of digitalization and traditional industrialization have gradually matured. Medical innovation and digital technology are progressing, and the deep integration of intensive care medicine and intelligence is surpassing the traditional informatization and ushering in new development opportunities. Technologies such as 5G, big data, artificial intelligence, and digital twins can help to understand more complex critical care issues, improve the diagnoses and prediction of diseases and symptoms, develop more accurate treatment strategies, and even transform the service model of critical care medicine. This paper summarizes the application and challenge of digital technology in the practical scenarios of critical care medicine, so as to further consolidate infrastructure, enrich application scenarios, accelerate implementation, improve effectiveness, and strengthen the safety and compliance with the regulations. |
| Key words: digital intelligence integration critical care medicine artificial intelligence digital twin big data |
