Publications by authors named "D Alis"
The rapid evolution of artificial intelligence (AI), particularly in deep learning, has significantly impacted radiology, introducing an array of AI solutions for interpretative tasks. This paper provides radiology departments with a practical guide for selecting and integrating AI solutions, focusing on interpretative tasks that require the active involvement of radiologists. Our approach is not to list available applications or review scientific evidence, as this information is readily available in previous studies; instead, we concentrate on the essential factors radiology departments must consider when choosing AI solutions.
View Article and Find Full Text PDFBackground: Explainable Artificial Intelligence (XAI) is prominent in the diagnostics of opaque deep learning (DL) models, especially in medical imaging. Saliency methods are commonly used, yet there's a lack of quantitative evidence regarding their performance.
Objectives: To quantitatively evaluate the performance of widely utilized saliency XAI methods in the task of breast cancer detection on mammograms.
Background: Being digitally literate allows health-based science students to access reliable, up-to-date information efficiently and expands the capacity for continuous learning. Digital literacy facilitates effective communication and collaboration among other healthcare providers. It helps to navigate the ethical implications of using digital technologies and aids the use of digital tools in managing healthcare processes.
View Article and Find Full Text PDFObjective: Robot-assisted minimally invasive coronary bypass surgery is one of the least invasive approaches that offers multivessel revascularization and accelerated recovery. We investigated the benefits of computed tomography angiography (CTA) guidance in robotic coronary bypass (RCAB) by analyzing perioperative outcomes.
Methods: Between April 2022 and April 2023, 60 consecutive patients who underwent RCAB under preoperative CTA guidance were included.