Application Effect of Mammography Combined With AI Diagnosis Teaching Mode in the Standardized Training of Residents in Radiology Department
Objective To explore the application effect of mammography combined with artificial intelligence(AI)diagnosis teaching mode in the standardized training of residents in radiology department.Methods A total of 50 residents who received standardized training of residents in department of radiology,Mindong Hospital of Ningde City were selected from January 2019 to December 2022 as the research subjects,and were divided into observation group(adopting mammography combined with AI diagnosis teaching mode)and control group(adopting mammography teaching mode)according to different teaching methods,with 25 cases in each group.The clinical diagnosis coincidence rate,teaching quality,learning motivation,learning satisfaction and clinical thinking ability of the two groups were observed after training.Results After training,the diagnostic coincidence rate in the observation group was 88.00%,which was higher than 64.00%in the control group,the difference was statistically significant(P<0.05).After training,the scores of language expression,teacher-student communication and teaching atmosphere of resident teaching quality were(95.07±2.21)points,(92.02±2.56)points and(93.48±1.43)points in the observation group,which were higher than(92.04±2.23)points,(87.34±2.48)points and(91.44±1.53)points in the control group,while the score of learning difficulty was(13.47±1.48)points in the observation group,which was lower than(14.23±0.43)points in the control group,the difference was statistically significant(P<0.05).The scores of competency need,independent need,attribution need and learning satisfaction of resident learning motivation in the observation group were(9.07±1.21)points,(13.27±0.13)points,(12.48±1.43)points and(21.47±1.48)points,which were higher than(8.15±1.24)points,(12.85±0.24)points,(11.44±1.53)points and(19.23±1.43)points in the control group,the difference was statistically significant(P<0.05).The scores of criticism,systematicness and evidence of clinical thinking ability in the observation group were(23.26±1.22)points,(41.47±1.12)points and(26.12±0.47)points,which were higher than(20.51±1.49)points,(37.23±1.43)points and(23.93±0.87)points in the control group,the difference was statistically significant(P<0.001).Conclusion The adoption of mammography combined with AI diagnosis teaching mode can improve the coincidence rate of clinical diagnosis and clinical thinking ability of residents,and enhance the learning satisfaction.
artificial intelligence diagnosis systembreast cancerstandardized training for resident doctorsclinical thinking abilitylearning motivationlearning satisfaction
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维普
