Deep Learning Models Classify Disease From Medical Imaging

THURSDAY, Sept. 26, 2019 (HealthDay News) -- Early evidence suggests that diagnostic performance of deep learning models is equivalent to that of health care professionals for interpreting medical imaging, according to a study published online Sept. 25 in The Lancet Digital Health. Xiaoxuan Liu, M.B.Ch.B., from the University Hospitals Birmingham NHS Foundation Trust in the United Kingdom, and colleagues conducted a systematic review and meta-analysis to assess the diagnostic accuracy of deep learning algorithms versus health care professionals in classifying disease using medical imaging. Binary diagnostic accuracy data were extracted and contingency tables were constructed to derive the outcomes of interest: sensitivity and specificity. Data from 82 studies, describing 147 patient cohorts were included. The researchers found that based on 69 studies, sensitivity ranged from 9.7 to 100 percent and specificity ranged from 38.9 to 100 percent.