Heavy metals pose a significant threat to human health, with contaminated water sources linked to severe conditions, including gastric cancer. Consequently, the effective remediation of heavy metals is crucial. This study employs a bibliographic analysis to examine key methodologies, leading organizations, and prominent countries involved in heavy metal remediation. By systematically reviewing around 1,000 records, the paper identifies the most critical remediation techniques and provides a comprehensive overview of current practices in the field. Additionally, the study explores prospects, emphasizing the potential of emerging technologies such as big data and machine learning to enhance remediation efforts. It highlights recent advancements, identifies significant trends, such as the growing use of bioremediation and nanotechnology, and addresses critical challenges in the remediation landscape, including regulatory hurdles and technological limitations. By making stronger connections between the identified trends and their implications for future research, this comprehensive analysis aims to provide valuable insights and guide the development of improved strategies for mitigating the impact of heavy metal contamination, ultimately safeguarding public health.
Keywords: bibliographic study; heavy metals; machine learning; remediation; water pollution.
© 2025 The Authors This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/).