人工智能在老年医学教学中的应用现状及前景

doi:10.3969/j.issn.1003-9198.2025.07.022

Abstract

Abstract: With the rapid development of artificial intelligence (AI) technology, its application in geriatric medicine teaching is becoming more and more widespread, bringing revolutionary changes to medical education. This paper introduces the current status of AI application in comprehensive geriatric assessment, geriatric clinical internship teaching, and the whole management of geriatric patients’ conditions, and discusses how to reasonably integrate AI technology into the teaching process of geriatrics at different learning stages. This paper further explores the challenges encountered by AI in geriatrics education, covering the topics of data quality and privacy protection, technology and ethics, and the impact on teachers and students. Looking ahead, AI technology has a promising future in geriatric medicine teaching, especially in terms of technology trends, changes in teaching models, and policy and regulatory support. In conclusion, AI technology is expected to further improve the quality and efficiency of geriatrics teaching and provide strong support for cultivating the next generation of medical talents.

Key words: artificial intelligence, geriatrics, medical education, teaching innovation, technological challenges, prospective trends

CLC Number:

TP18
R592

WANG Yang, LI Daiping, YANG Yanwu, HE Bofei, YUE Jirong, DONG Birong, GE Meiling. Current status and prospects of the application of artificial intelligence in geriatric medicine teaching[J]. Practical Geriatrics, 2025, 39(7): 753-756.

References

[1] 民政部, 全国老龄办. 2023年度国家老龄事业发展公报[R/OL]. (2024-10-12). [2024-11-20] . https://www.gov.cn/lianbo/bumen/202410/content_6979487.htm.
[2] 邹蕾, 张先锋. 人工智能及其发展应用[J]. 信息网络安全, 2012, 12(2): 11-13.
[3] 李玉晓. 人工智能技术在融合媒体系统中的研究与应用[J]. 广播电视信息, 2023, 30(6): 54-56.
[4] 施红, 赵烨婧, 邓琳子. 老年综合评估的临床意义与应用进展[J]. 中国心血管杂志, 2021, 26(5): 413-417.
[5] TANG L K, MA J, LI Y M, et al. Health monitoring of movement disorder subject based on diamond stacked sparse autoencoder ensemble model[EB/OL]. (2023-03-15)[2024-10-20] . http://arxiv.org/abs/2303.08538.
[6] WANG Y, CUI H, LI L, et al. Digitalization of prevention and treatment and the combination of western and Chinese medicine in management of acute heart failure[J]. Front Cardiovasc Med, 2023, 10: 1146941.
[7] PENG G C Y, ALBER M, TEPOLE A B, et al. Multiscale modeling meets machine learning: what can we learn?[J]. Arch Comput Methods Eng, 2021, 28(3): 1017-1037.
[8] GAO H, YOUS M L, CONNELLY D, et al. Implementation and impacts of virtual team-based care planning for older persons in formal care settings: a scoping review[J]. Digit Health, 2023, 9: 20552076231151567.
[9] CROWE C, BARTON J, O’FLYNN B, et al. Association between wrist-worn free-living accelerometry and hand grip strength in middle-aged and older adults[J]. Aging Clin Exp Res, 2024, 36(1): 108.
[10] 杨蓝, 胡健康. 肌肉减少症现状、早期筛查和预防性治疗研究进展社区思考[J]. 中国社区医师, 2024, 40(27): 16-18.
[11] 倪晨旭, 汤佳, 邵宝魁, 等. 智能穿戴设备与老年健康: 来自智能手环的证据[J]. 人口学刊, 2023, 45(6): 50-67.
[12] THOMPSON S, METCALFE K, BONCEY K, et al. Interprofessional education in geriatric medicine: towards best practice. A controlled before-after study of medical and nursing students[J]. BMJ Open, 2020, 10(1): e018041.
[13] MARIËLLE VAN WIJNGAARDEN M T, DIENEKE VAN ASSELT D B, SIETSKE GROL S M, et al. Components and outcomes in under- and postgraduate medical education to prepare for the delivery of integrated care for the elderly: a scoping review[J]. Int J Integr Care, 2023, 23(2): 7.
[14] 邢云利, 王珊, 孙颖. 多学科联合教学在老年医学住院医师规范化培训中的应用探讨[J]. 中国医药, 2022, 17(7): 1092-1094.
[15] PARCHMANN N, HANSEN D, ORZECHOWSKI M, et al. An ethical assessment of professional opinions on concerns, chances, and limitations of the implementation of an artificial intelligence-based technology into the geriatric patient treatment and continuity of care[J]. Geroscience, 2024, 46(6): 6269-6282.
[16] RATTANAWIBOOMSOM V, TALPUR S R. Enhancing health monitoring and active aging in the elderly population: a study on wearable technology and technology-assisted care[J]. Int J Online Biomed, 2023, 19(11): 173-186.
[17] SHAFI S, PARWANI A V. Artificial intelligence in diagnostic pathology[J]. Diagn Pathol, 2023, 18(1): 109.
[18] 郭联山, 李政钊. 人工智能在急危重症患者诊治中应用研究进展[J]. 中国急救医学, 2023, 43(10): 837-840.
[19] CHEN Z, CHEN Y, SUN Y, et al. Predicting gastric cancer response to anti-HER2 therapy or anti-HER2 combined immunotherapy based on multi-modal data[J]. Signal Transduct Target Ther, 2024, 9(1): 222.
[20] 程珊, 丛林, 胡文东, 等. “AI+教育” 时代背景下医学实践课程教学模式现状与改革趋势[J]. 医学新知, 2024, 34(8): 950-956.

Current status and prospects of the application of artificial intelligence in geriatric medicine teaching

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