Objective Verification of artificial intelligence(artificial)based on computer aided diagnosis system of pulmonary infection.The accuracy and feasibility of intelligence,AI technique in the detection and evaluation of invasive pulmonary tuberculosis.Methods A total of 120 patients with invasive pulmonary tuberculosis diagnosed for the first time in Yan'an second people's Hospital from January 2020 to July 2022 were collected retrospectively.The lesion range of each lung lobe and the lesion sign score were added to get the final score.Pearson or Spearman correlation analysis was used to analyze the correlation between the visual score of the whole lung and each lobe(lesion range score,lesion severity score,sign score)and CT quantitative index[lesion volume(lesion Volume,LeV/ml),percentage of lesion to lung volume(per-centage of lesion,LeV%)and lesion mass(lesion mass,LM/g)].Results The whole lung lesion range score and lesion severity score were highly correlated with the whole lung quantitative CT index LeV,LeV%and LM(r =0.783-0.826,P<0.001),and the LeV%score of each lobe was highly correlated with the lesion proportion score and the LM score of each lobe with the lesion severity score evaluated by manual(r =0.761-0.913,P<0.001).Conclusion The CT quan-titative indexes of wh1ole lung and each lobe obtained by AI are highly correlated with the traditional visual score,which proves that it is accurate and feasible in the objective imaging quantitative evaluation of invasive pulmonary tuberculosis.
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