利用树状结构 3D CNN 和视觉变换器模型，基于手掌苍白视频进行无创贫血检测

IF 1.7 4区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Journal of Experimental & Theoretical Artificial Intelligence Pub Date : 2024-01-08 DOI:10.1080/0952813x.2023.2301401

Abhishek Kesarwani, Sunanda Das, Dakshina Ranjan Kisku, Mamata Dalui

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引用次数: 0

摘要

贫血是一种常见疾病，影响着全球数十亿人，其原因是血红蛋白水平过低。根据世卫组织的统计，贫血在发展中国家和发展中国家的发病率最高。

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Non-invasive anaemia detection based on palm pallor video using tree-structured 3D CNN and vision transformer models

Anaemia is a common disease that affects billions of people worldwide and is caused due to low blood haemoglobin level. According to WHO statistics, anaemia is the most prevalent in developing and ...

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来源期刊

Journal of Experimental & Theoretical Artificial Intelligence 工程技术-计算机：人工智能

CiteScore

6.10

自引率

4.50%

发文量

审稿时长

>12 weeks

期刊介绍： Journal of Experimental & Theoretical Artificial Intelligence (JETAI) is a world leading journal dedicated to publishing high quality, rigorously reviewed, original papers in artificial intelligence (AI) research. The journal features work in all subfields of AI research and accepts both theoretical and applied research. Topics covered include, but are not limited to, the following: • cognitive science • games • learning • knowledge representation • memory and neural system modelling • perception • problem-solving