Deep learning in medical image analysis: introduction to underlying principles and reviewer guide using diagnostic case studies in paediatrics

Abstract

Deep learning, a subset of artificial intelligence, has gained attention in recent years for its ability to achieve human level performance in medical image analysis. As deep learning is increasingly being studied in medical image analysis, it is essential that clinicians are familiar with its underlying principles, strengths, and possible pitfalls in their evaluation. This article aims to clarify deep learning techniques applied in medical image analysis and to help frontline clinicians understand how to read and appraise studies about this new and rapidly advancing technology. While image analysis using deep learning has the potential to enhance the diagnosis of various medical conditions, clinicians, policy makers, and patients should exercise caution when evaluating the available evidence.

Ähnliche Arbeiten