… We developed a deep learning model, named FracNet, to detect and segment rib fractures.
720, 60 and 120 patients were randomly split as training cohort, tuning cohort and test cohort…

… ■ Studies of deep learning algorithms for radiologic diagnosis … that performed external
validation over a 6-year period. … Therefore, our results do not necessarily apply to these other …

… model development and validation: … findings along with a head-to-head comparison of the
model performance with a team of neurologists underscored the validity of the deep learning …

… To evaluate the ability of a deep learning system (DLS) to grade diagnostic prostate biopsy
… In subanalyses of biopsy specimens from an external validation set (n = 322), the Gleason …

… The results of our pilot study proved that the deep learning network model (DeepSurv)
performed better than conventional linear regression modeling (TNM staging model) in …

… results suggest that transfer learning for a 2D deep learning framework can be robustly applied
to deep learning … a 3D framework because 3D deep learning requires significantly higher …

… To allay concerns about effects of immortal time bias and censoring on the results, we
recorded the ultimate outcome of each patient who was admitted in this time frame, even if the …

… We developed and validated a deep-learning algorithm for polyp detection. We used a …
These findings suggest that our automatic polyp detection algorithm is practical and accurate. In …

… Machine learning modalities integrating findings from these common laboratory test results
… , we sought to describe the development of a machine learning model for ruling out COVID-…

… results were frequently reported from nucleic acid testing, we aimed to test whether the algorithm
could detect … These CT results were taken on the same day as the nucleic acid tests (Fig…