Potential of E-Learning Interventions and Artificial Intelligence-Assisted Contouring Skills in Radiotherapy: The ELAISA Study - Rasmussen, Mathis Ersted; Akbarov, Kamal; Titovich, Egor; Nijkamp, Jasper Albertus; Van Elmpt, Wouter; Primdahl, Hanne; Lassen, Pernille; Cacicedo, Jon; Cordero-Mendez, Lisbeth; Uddin, A F M Kamal; Mohamed, Ahmed; Prajogi, Ben; et al. (Lippincott, Williams & Wilkins, 2024)
Most research on artificial intelligence-based auto-contouring as template (AI-assisted contouring) for organs-at-risk (OARs) stem from high-income countries. The effect and safety are, however, likely to depend on local factors. This study aimed to investigate the effects of AI-assisted contouring and teaching on contouring time and contour quality among radiation oncologists (ROs) working in low- and middle-income countries (LMICs).
Keywords: e-learning; Artificial Intelligence; Assisted Contouring Skills in Radiotherapy