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Insights into Imaging

Table 4 Logistic regression analyses on the association of increased workload with a study’s research area and impact factor of the journal in which the study was published, for an academic tertiary care center

From: Workload of diagnostic radiologists in the foreseeable future based on recent scientific advances: growth expectations and role of artificial intelligence

Variable Univariate analysis Multivariate analysis
OR 95% CI p value OR 95% CI p value
Study’s research areaa 11.79b 3.64–38.28b  < 0.001b 10.64b 3.25–34.80b  < 0.001b
Impact factor of the journal in which the study was publishedc 0.93d 0.86–1.00d 0.020 0.93d 0.85–1.02d 0.110
  1. CI: confidence interval, OR: odds ratio
  2. aBased on 286 studies with the following primary research areas: artificial intelligence (n = 38), breast (n = 16), cardiac (n = 32), chest (n = 20), computed tomography (n = 4), emergency (n = 1), gastrointestinal–abdominal (n = 21), head–neck (n = 6), magnetic resonance (n = 3), multisystem (n = 1), musculoskeletal (n = 18), neuroradiology (n = 46), nuclear medicine (n = 51), oncology (n = 2), pediatric (n = 2), ultrasonography (n = 2), urogenital (n = 17), and vascular (n = 6)
  3. bStudies with artificial intelligence as research area were significantly associated with increased workload
  4. cBased on 26 individual journals with a median impact factor of 5.061 (range: 2.687–33.752)
  5. dPer unit increase in impact factor
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