Artificial intelligence for disease diagnostics still has a long way to go

IF 1.4 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING World journal of radiology Pub Date : 2024-03-28 DOI:10.4329/wjr.v16.i3.69
Jian-She Yang, Qiang Wang, Zhong-Wei Lv
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Abstract

Artificial intelligence (AI) can sometimes resolve difficulties that other advanced technologies and humans cannot. In medical diagnostics, AI has the advantage of processing figure recognition, especially for images with similar characteristics that are difficult to distinguish with the naked eye. However, the mechanisms of this advanced technique should be well-addressed to elucidate clinical issues. In this letter, regarding an original study presented by Takayama et al , we suggest that the authors should effectively illustrate the mechanism and detailed procedure that artificial intelligence techniques processing the acquired images, including the recognition of non-obvious difference between the normal parts and pathological ones, which were impossible to be distinguished by naked eyes, such as the basic constitutional elements of pixels and grayscale, special molecules or even some metal ions which involved into the diseases occurrence.
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用于疾病诊断的人工智能还有很长的路要走
人工智能(AI)有时可以解决其他先进技术和人类无法解决的难题。在医疗诊断中,人工智能在处理图形识别方面具有优势,特别是对于肉眼难以分辨的具有相似特征的图像。然而,这种先进技术的机制应该得到很好的解决,以阐明临床问题。在这封信中,针对高山等人提出的一项原创性研究,我们建议作者应有效说明人工智能技术处理所获图像的机制和详细过程,包括识别正常部分和病理部分之间的非明显差异,这些差异是肉眼无法区分的,例如像素和灰度的基本组成元素、特殊分子,甚至一些与疾病发生有关的金属离子。
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来源期刊
World journal of radiology
World journal of radiology RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
自引率
8.00%
发文量
35
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