分化型甲状腺癌人工智能语音随访系统的构建及应用

郭丝锦; 延常姣; 王洋; 曹小花; 王廷

doi:10.7619/jcmp.20241127

分化型甲状腺癌人工智能语音随访系统的构建及应用

中国人民解放军空军军医大学第一附属医院甲乳血管外科, 陕西西安, 710032

基金项目:

陕西省重点研发项目 2021JZ-29

详细信息

通讯作者:
王廷, E-mail: ting_w100@126.com

中图分类号: R736.1;R472;R319
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- 文章访问数: 155
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- PDF下载量: 19
出版历程
- 收稿日期: 2024-03-17
- 修回日期: 2024-05-23
- 刊出日期: 2024-08-27

Establishment and application of artificial intelligence voice follow-up system for differentiated thyroid cancer

Department of Thyroid and Breast Vascular Surgery, the First Affiliated Hospital of Air Force Medical University of the Chinese People's Liberation Army, Xi'an, Shaanxi, 710032

摘要

摘要:
目的
构建分化型甲状腺癌人工智能语音随访系统，评价该系统信息采集的完整性和准确性。
方法
根据分化型甲状腺癌患者术后用药及复查情况，构建分化型甲状腺癌人工智能语音随访系统。对2024年2月25—29日本院甲乳血管外科甲状腺癌数据库管理系统中未进行随访的2 471例分化型甲状腺癌患者进行电话随访，并随机抽取10%, 对220例患者的通话记录进行完整性和准确性分析。
结果
本研究成功构建分化型甲状腺癌人工智能语音随访系统，总体电话接通率为88.9%。对于呼叫成功的患者，人工智能语音随访系统的随访平均用时(1.7±0.5) min, 总体信息采集完整率为83.8%, 术后3个月随访信息采集完整率为92.9%, 术后长期随访信息采集完整率为82.7%, 差异有统计学意义(χ²=15.200, P < 0.001)。该随访系统信息采集准确率为94.1%。说方言随访者和说普通话随访者的信息采集准确率分别为92.2%和95.4%, 差异无统计学意义(χ²=0.957, P=0.389)。
结论
分化型甲状腺癌人工智能语音随访系统具有较高的信息采集效率、完整性和准确性, 可降低随访人力成本，在大规模分化型甲状腺癌人群随访中具有良好的应用前景。
- 分化型甲状腺癌 /
- 人工智能 /
- 随访系统 /
- 电话随访 /
- 信息采集
Abstract:
Objective
To establish an artificial intelligence voice follow-up system for differentiated thyroid cancer and evaluate the completeness and accuracy of information collection by this system.
Methods
Based on the postoperative medication and follow-up status of patients with differentiated thyroid cancer, an artificial intelligence voice follow-up system for differentiated thyroid cancer was established. From February 25 to 29, 2024, a total of 2, 471 differentiated thyroid cancer patients without follow-up in the thyroid cancer database management system of the Department of Thyroid and Breast Vascular Surgery of the Hospital were followed up by telephone, and 220 patients (approximately 10% of the total) were randomly selected for completeness and accuracy analyses of their call records.
Results
This study successfully established an artificial intelligence voice follow-up system for differentiated thyroid cancer, and the overall call connection rate was 88.9%. For patients with successful calls, the average follow-up time of the artificial intelligence voice follow-up system was (1.7±0.5) minutes, the overall information collection completeness rate was 83.8%, with a completeness rate of 92.9% for follow-up at 3 months after surgery and 82.7% for long-term follow-up, and the differences were statistically significant (χ²=15.200, P < 0.001). The accuracy rate of information collection by this follow-up system was 94.1%. The accuracy rates of information collection for patients who spoke dialect and Mandarin during follow-up were 92.2% and 95.4% respectively, and the difference was not statistically significant (χ²=0.957, P=0.389).
Conclusion
The artificial intelligence voice follow-up system for differentiated thyroid cancer has high efficiency, completeness, and accuracy in information collection, which can reduce human costs for follow-up and has good application prospects in large-scale follow-up of populations with differentiated thyroid cancer.
- differentiated thyroid cancer /
- artificial intelligence /
- follow-up system /
- telephone follow-up /
- information collection

HTML全文

图 1 分化型甲状腺癌患者术后3个月人工智能语音随访话术模板

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图 2 分化型甲状腺癌患者人工智能语音长期随访话术模板

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图 3 随访流程技术路线图

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