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ZHAO Chenghua. Value of artificial intelligence assisted diagnostic system combined with CT test in diagnosis of pulmonary nodules[J]. Journal of Clinical Medicine in Practice, 2020, 24(19): 9-11. DOI: 10.7619/jcmp.202019003
Citation: ZHAO Chenghua. Value of artificial intelligence assisted diagnostic system combined with CT test in diagnosis of pulmonary nodules[J]. Journal of Clinical Medicine in Practice, 2020, 24(19): 9-11. DOI: 10.7619/jcmp.202019003
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Value of artificial intelligence assisted diagnostic system combined with CT test in diagnosis of pulmonary nodules

  • Department of Cardiothoracic Surgery, Xinxiang City First People's Hospital in Henan Province, Xinxiang, Henan, 453000

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  • Received Date: July 19, 2020
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    • Abstract
  • Objective To explore the application value of artificial intelligence(AI)assisted diagnostic system combined with CT test in diagnosis of pulmonary nodules. Methods A total of 100 patients with pulmonary nodules were selected and conducted with CT test, AI assisted diagnostic system and CT test in combination. The detection status and time of pulmonary nodules were compared between the two methods. According to the pathological results, the diagnostic efficiency of the two methods was evaluated. Results The detection rate of pulmonary nodules by AI assisted diagnostic system combined with CT test was 97.00%(97/100), which was significantly higher than 86.00%(86/100)by CT test(P<0.05). The average detection time of pulmonary nodules by AI assisted diagnostic system combined with CT test was(391.15±156.08)s, which was significantly shorter than(482.71±248.03)s by CT test(P<0.05). The accuracy, sensitivity and specificity of AI assisted diagnostic system combined with CT test were significantly higher than those of CT test in the diagnosis of malignant pulmonary nodules, and the missed diagnosis rate and misdiagnosis rate were significantly lower than those of CT test(P<0.05). Conclusion Application of AI assisted diagnostic system combined with CT test can effectively detect pulmonary nodules, reduce the missed diagnosis rate and increase the diagnostic efficiency for malignant pulmonary nodules.
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