| 摘 要: 针对手指V-Y皮瓣传统诊疗模式中皮瓣设计精度不足、术中血管损伤风险高、术后监测滞后及预后评估片面等问题,围绕计算机与AI技术的应用展开,旨在优化诊疗全流程。术前通过计算机三维重建与AI建模实现血管定位及皮瓣虚拟规划,将设计误差从15% 降至8%;术中依托 AI导航与血流监测,使血管蒂损伤率降至8%,缺血预警灵敏度提升至85%;术后构建多模态 AI预警体系,缩短血管危象发现时间至2h,干预成功率提升20%;同时,建立 AI康复推荐与预后模型,术后6个月患者关节活动度优良率达82%以上。临床验证表明,该技术体系可突破传统局限,为诊疗精准化提供可靠方案。 |
| 关键词: 手指V-Y皮瓣 计算机技术 人工智能 诊疗优化 预后评估 |
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中图分类号:
文献标识码: A
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| 基金项目: 国家自然科学基金资助项目(52279069) |
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| Optimization Study on Diagnosis and Treatment of Finger V-Y Flaps Based on Computer and AI Echnologies |
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LV Bing1, ZHANG Ying2
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(1.Department of Emergency, The Fourth Afiliated Hospital of Harbin Medical University, Harbin 150001, China;
2.Department of Tuberculosis, Harbin Chest Hospital, Harbin 150026, China)
57874266@qq.com; 315054718@qq.com
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| Abstract: Aiming at the problems in the traditional diagnosis and treatment mode of finger V-Y flaps, such as insufficient flap design accuracy, high risk of intraoperative vascular injury, delayed postoperative monitoring and one-sided prognosis evaluation, this study focuses on the application of computer and AI technologies to optimize the entire diagnosis and treatment process. Preoperatively, computer 3D reconstruction and AI model were used to realize vascular localization and virtual flap planning, reducing the design error from 15% to 8% . Intraoperatively, relying on AI navigation and blood flow monitoring, the vascular pedicle injury rate was reduced to 8%, and the ischemia early warning sensitivity was increased to 85% . Postoperatively, a multimodal AI early warning system was constructed to shorten the detection time of vascular crisis to 2 hours and increase the intervention success rate by 20% . At the same time, an AI rehabilitation recommendation and
prognosis model was established, and the excellent and good rate of joint mobility of patients reached over 82% at 6 months after surgery. Clinical verification shows that this technical system can break through traditional limitations and provide a
reliable scheme for the precision of diagnosis and treatment. |
| Keywords: finger V-Y flap computer technology artificial intelligence diagnosis and treatment optimization prognosis evaluation |
