Page 125 - 《中国药房》2024年4期
P. 125
和推进数据共享的重要性,这预示着通过拓宽数据来源 研究思考[J]. 中国中药杂志,2020,45(14):3331-3335.
获取高质量数据将有望成为医院药学服务领域研究与 WANG L X,XIE Y M. Study on precise mechanism of
应用的关键动力。 Chinese patent medicine from perspective of activating
4 结语 data[J]. China J Chin Mater Med,2020,45(14):3331-
3335.
随着科技的飞速发展,AI已成为推动现代医疗进步
[10] 陈悦,陈超美,刘则渊,等. CiteSpace知识图谱的方法论
的关键力量。本研究通过文献计量学分析,揭示了AI在
功能[J]. 科学学研究,2015,33(2):242-253.
医院药学服务应用研究的趋势与挑战。AI 虽为药学服
CHEN Y,CHEN C M,LIU Z Y,et al. The methodology
务带来了前所未有的机遇,但同时也伴随着跨学科知识 function of CiteSpace mapping knowledge domains[J].
整合和数据处理能力方面的新挑战。药学工作者需要 Stud Sci Sci,2015,33(2):242-253.
不断提升自身的技术能力,以适应这一变革。展望未 [11] JAGANNATHA A,LIU F F,LIU W S,et al. Overview of
来,期待AI能更深入地融入医疗卫生领域,助力药学服 the first natural language processing challenge for extrac-
务的精准化、高效化和安全化发展,进而为全球健康事 ting medication,indication,and adverse drug events from
业的发展做出更大贡献。 electronic health record notes:MADE 1.0[J]. Drug Saf,
参考文献 2019,42(1):99-111.
[12] GULSHAN V,PENG L,CORAM M,et al. Development
[ 1 ] BENKE K,BENKE G. Artificial intelligence and big data
and validation of a deep learning algorithm for detection
in public health[J]. Int J Environ Res Public Health,2018,
of diabetic retinopathy in retinal fundus photographs[J].
15(12):2796.
JAMA,2016,316(22):2402-2410.
[ 2 ] CERCHIA C,LAVECCHIA A. New avenues in artificial-
[13] 凌曦,赵志刚,李新刚 . 人工智能技术在药学领域的应
intelligence-assisted drug discovery[J]. Drug Discov To‐
用:基于 Web of Science 的文献可视化分析[J]. 中国药
day,2023,28(4):103516.
房,2019,30(4):433-438.
[ 3 ] POULOS R C,CAI Z X,ROBINSON P J,et al. Opportu‐
LING X,ZHAO Z G,LI X G. Application of artificial in‐
nities for pharmacoproteomics in biomarker discovery[J].
telligence technology in pharmaceutical field:visualiza‐
Proteomics,2023,23(7/8):e2200031.
tion analysis of literature based on web of science[J].
[ 4 ] JUMPER J,EVANS R,PRITZEL A,et al. Highly accu‐
China Pharm,2019,30(4):433-438.
rate protein structure prediction with AlphaFold[J]. Na‐
[14] 高曼,李海燕.中医药信息学应用研究热点[J].首都医科
ture,2021,596(7873):583-589.
大学学报,2022,43(4):592-599.
[ 5 ] RANCHON F,CHANOINE S,LAMBERT-LACROIX S,
GAO M,LI H Y. Application research hotspot of tradi‐
et al. Development of artificial intelligence powered APPs
tional Chinese medicine informatics[J]. J Cap Med Univ,
and tools for clinical pharmacy services:a systematic re‐
2022,43(4):592-599.
view[J]. Int J Med Inform,2023,172:104983.
[15] 孙忠人,游小晴,韩其琛,等. 人工智能在中医药领域的
[ 6 ] 陈井泉,刘燕 . 智慧门诊药房的建立与实践[J]. 医药导
应用进展及现状思考[J]. 世界科学技术-中医药现代化,
报,2022,41(9):1393-1396.
2021,23(6):1803-1811.
CHEN J Q,LIU Y. Practice and establishment of smart
SUN Z R,YOU X Q,HAN Q C,et al. Progress and cur‐
outpatient pharmacy[J]. Her Med,2022,41(9):1393-
rent considerations of artificial intelligence in the field of
1396.
traditional Chinese medicine[J]. Mod Tradit Chin Med
[ 7 ] GUMBO T,CHIGUTSA E,PASIPANODYA J,et al. The Mater Med-World Sci Technol,2021,23(6):1803-1811.
pyrazinamide susceptibility breakpoint above which com‐ [16] JORDAN M I,MITCHELL T M. Machine learning:
bination therapy fails[J]. J Antimicrob Chemother,2014, trends,perspectives,and prospects[J]. Science,2015,349
69(9):2420-2425. (6245):255-260.
[ 8 ] LIU Y G,MOODLEY M,PASIPANODYA J G,et al. De‐ [17] CALIFF R M,ROBB M A,BINDMAN A B,et al. Trans‐
termining the delamanid pharmacokinetics/pharmacody‐ forming evidence generation to support health and health
namics susceptibility breakpoint using Monte Carlo ex‐ care decisions[J]. N Engl J Med,2016,375(24):2395-
periments[J]. Antimicrob Agents Chemother,2023,67 2400.
(4):e0140122. (收稿日期:2023-07-12 修回日期:2024-01-19)
[ 9 ] 王连心,谢雁鸣. 激活数据学视角下的中成药精准机制 (编辑:孙 冰)
中国药房 2024年第35卷第4期 China Pharmacy 2024 Vol. 35 No. 4 · 499 ·