RESUMEN
As radiology is inherently a data-driven specialty, it is especially conducive to utilizing data processing techniques. One such technique, deep learning (DL), has become a remarkably powerful tool for image processing in recent years. In this work, the Association of University Radiologists Radiology Research Alliance Task Force on Deep Learning provides an overview of DL for the radiologist. This article aims to present an overview of DL in a manner that is understandable to radiologists; to examine past, present, and future applications; as well as to evaluate how radiologists may benefit from this remarkable new tool. We describe several areas within radiology in which DL techniques are having the most significant impact: lesion or disease detection, classification, quantification, and segmentation. The legal and ethical hurdles to implementation are also discussed. By taking advantage of this powerful tool, radiologists can become increasingly more accurate in their interpretations with fewer errors and spend more time to focus on patient care.
Asunto(s)
Aprendizaje Profundo , Radiología , Humanos , Procesamiento de Imagen Asistido por ComputadorRESUMEN
Online social networking services have changed the way we interact as a society and offer many opportunities to improve the way we practice radiology and medicine in general. This article begins with an introduction to social networking. Next, the latest advances in online social networking are reviewed, and areas where radiologists and clinicians may benefit from these new tools are discussed. This article concludes with several steps that the interested reader can take to become more involved in online social networking.
Asunto(s)
Instrucción por Computador/métodos , Difusión de la Información/métodos , Internet/estadística & datos numéricos , Relaciones Interprofesionales , Educación del Paciente como Asunto/métodos , Radiología/organización & administración , Apoyo Social , Sistemas en Línea , Relaciones Médico-PacienteRESUMEN
The rapid advances in mobile computing technology have the potential to change the way radiology and medicine as a whole are practiced. Several mobile computing advances have not yet found application to the practice of radiology, while others have already been applied to radiology but are not in widespread clinical use. This review addresses several areas where radiology and medicine in general may benefit from adoption of the latest mobile computing technologies and speculates on potential future applications.