Prínos Bayesovy statistické teorie pro diagnostiku maligních a nemaligních onemocnĕní plic, pleury a mediastina
[The Bayesian statistical theory in the diagnosis of malignant and non-malignant diseases of the lung, pleura and mediastinum]

. 1993 Oct 25 ; 132 (20) : 609-15.

Jazyk čeština Země Česko Médium print

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/pmid08269461
Odkazy

PubMed 8269461

The Bayesian algorithm was used to assess the probable diagnosis in 1262 patients with a recently diagnosed finding on X-rays of the chest and the results were compared with the final diagnosis. The patients were with regard to the X-ray picture divided into 9 groups: hilar, solitary, multiple, segmental, non-segmental, cavity, diffuse, pleural and mediastinal lesions. Using the Bayesian algorithm, commonly accessible factors were processed: age, sex, case-history, cigarette smoking, red cell sedimentation rate, number of leucocytes and diameter of solitary parenchymatous lesions and the impact of these factors for assessment of probability of a malignant or non-malignant lesion was evaluated. The reliability in different X-ray lesions was within the range of 84.2% to 92.4%. The authors evaluated also tests of sensitivity, specificity, the reliability of forecast of a positive and negative result, which confirmed the differences in the different groups which showed evaluated. Analysis of the results, provided evidence that the Bayesian algorithm is a promising objective method for the forecast of a malignant or non-malignant diagnosis in patients with a newly diagnosed X-ray finding of the chest.

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