Ramesh Priyanka, Karuppasamy Ramanathan, Veerappapillai Shanthi
Department of Biotechnology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, 632 014, Tamil Nadu, India.
Biomedicine (Taipei). 2020 Sep 11;10(3):5-17. doi: 10.37796/2211-8039.1012. eCollection 2020.
Artificial intelligence has illustrated drastic changes in radiology and medical imaging techniques which in turn led to tremendous changes in screening patterns. In particular, advancements in these techniques led to the development of computer aided detection (CAD) strategy. These approaches provided highly accurate diagnostic reports which served as a "second-opinion" to the radiologists. However, with significant advancements in artificial intelligence strategy, the diagnostic and classifying capabilities of CAD system are meeting the levels of radiologists and clinicians. Thus, it shifts the CAD system from second opinion approach to a high utility tool. This article reviews the strategies and algorithms developed using artificial intelligence for the foremost cancer diagnosis and classification which overcomes the challenges in the traditional method. In addition, the possible direction of AI in medical aspects is also discussed in this study.
人工智能已在放射学和医学成像技术方面引发了巨大变革，进而导致筛查模式发生了巨大变化。特别是，这些技术的进步促成了计算机辅助检测（CAD）策略的发展。这些方法提供了高度准确的诊断报告，为放射科医生提供了“第二种意见”。然而，随着人工智能策略的重大进展，CAD系统的诊断和分类能力正在达到放射科医生和临床医生的水平。因此，它将CAD系统从第二种意见方法转变为一种高效用工具。本文回顾了使用人工智能开发的用于首要癌症诊断和分类的策略和算法，这些策略和算法克服了传统方法中的挑战。此外，本研究还讨论了人工智能在医学方面可能的发展方向。
