Detecting Pulmonary Lesions in Low-Prevalence Real-World Settings Using Deep Learning. - Daniel Kvak; Anna Chromcová; Petra Ovesná; Jakub Dandár; Marek Biros; Robert Hrubý; Daniel Dufek; Marija Pajdakovic (MICAD, 2023)

Can Deep Learning Reliably Recognize Abnormality Patterns on Chest X-rays? A Multi-Reader Study Examining One Month of AI Implementation in Everyday Radiology Clinical Practice. - Daniel Kvak; Anna Chromcová; Petra Ovesná; Jakub Dandár; Marek Biros; Robert Hrubý; Daniel Dufek; Marija Pajdakovic (CoRR, 2023)

Evaluating the Performance of Deep Learning Model and Junior Radiologists in Reading Major Pathologies on Chest X-Rays: A Population-Based, Multi-reader Study. - Jakub Dandár; Jirí Gerold; Jan Krístek; Zdenek Straka; Daniel Kvak; Marek Biros; Robert Hrubý (MICAD, 2024)

Enhancing Diagnostic Accuracy in Fracture Identification on Musculoskeletal Radiographs Using Deep Learning: A Multi-Reader Retrospective Study. - Jakub Dandár; Michaela Skodová; Zdenek Straka; Daniel Kvak; Marek Biros (MICAD, 2024)

Multi-Centre Validation of a Deep Learning Model for Scoliosis Assessment. - Simon Kubov; Simon Klícník; Jakub Dandár; Zdenek Straka; Karolína Kvaková; Daniel Kvak (CoRR, 2025)