Fig. 1: Our proposed TORCH model framework.
From: Prediction of tumor origin in cancers of unknown primary origin with cytology-based deep learning
a, A total of 42,682 cases were sourced from three large tertiary referral institutions, 70% of which (n = 29,883) were used as training sets. Clinicopathological data were acquired from radiological imaging departments, medical records systems and pathological digital databases. b, During the diagnostic process, most images were magnified either ×200 or ×400. c, The deep-learning network, trained with cytological images, was aimed at dividing target images into five categories according to the highest predicted probability score. Classification results were further validated at four institutions, including three internal testing sets (n = 12,799) and two external testing sets (n = 14,538). N represents the N-th image tile.
