重金属检测中的人工智能:方法和伦理挑战

Nidhi Yadav , Brij Mohan Maurya , Dewan Chettri , Pooja , Chirag Pulwani , Mahesh Jajula , Savleen Singh kanda , Harysh Winster Suresh babu , Ajay Elangovan , Parthasarathy Velusamy , Mahalaxmi Iyer , Balachandar Vellingiri
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引用次数: 0

摘要

重金属是一种金属物质。它们通过自然和人类活动进入生物和非生物系统。这些有机污染物对大气、土壤和地下水都有影响,当它们进入食物链时,也会影响所有生物,尤其是人类。因此,监测并从环境和人类中清除HMs对于维持HMs毒性至关重要。原子吸附光谱法(AAS)和电感耦合等离子体质谱法(ICP-MS)等技术对环境和人体样品中的HMs进行了检测。随着基于人工智能的技术的进步,现在可以从环境和人类系统中检测并清除HMs。本文讨论了HMs对环境和人类健康的影响,它们的检测和去除技术,以及基于人工智能的技术在环境和人类样本中检测和去除HMs的最新进展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Artificial intelligence in heavy metals detection: Methodological and ethical challenges

Heavy metals (HMs) are metallic substances. They enter biotic and abiotic systems through natural and human activities. These HMs have an impact on the atmosphere, soil, and groundwater, and they also affect all living things, especially humans, when they enter the food chain. Therefore, monitoring and removing HMs from the environment and humans are crucial for maintaining HMs-based toxicity. The detection of HMs from environmental and human samples has been performed by techniques such as atomic adsorption spectrometry (AAS) and inductively coupled plasma mass spectrometry (ICP-MS). With the advancement of AI-based technology, HMs are now detected and removed from the environment and human systems. This review discusses the impact of HMs on the environment and human health, their detection and removal techniques, and the integration of recent advancements in AI-based technology for the detection and removal of HMs from environmental and human samples.

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来源期刊
Hygiene and environmental health advances
Hygiene and environmental health advances Environmental Science (General)
CiteScore
1.10
自引率
0.00%
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0
审稿时长
38 days
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