Combining spatial autocorrelation with artificial intelligence models to estimate spatial distribution and risks of heavy metal pollution in agricultural soils

Günal, Elif; Budak, Mesut; Kılıç, Miraç; Cemek, Bilal; Sırrı, Mesut

doi:10.1007/s10661-022-10813-2

Cited by 8 publications

(2 citation statements)

References 85 publications

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“…Within the domain of research methodologies, both domestic and international pursuits primarily deploy sophisticated frameworks, such as the geo-accumulation index, single-item pollution index, potential ecological risk index, Nemeiro comprehensive pollution index, and the enrichment factor method. These tools serve as instrumental means to evaluate the intricate landscape of heavy metal pollution within the soil [16,17]. Each of these methodologies possesses inherent advantages and drawbacks in its utilization.…”

Section: Literature Reviewmentioning

confidence: 99%

Characteristics of Soil Heavy Metal Pollution and Health Risks in Chenzhou City

Kuang,

Chen,

Zhu

2024

Processes

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The objective of this inquiry is to illuminate the attributes of heavy metal contamination and evaluate the potential ecological hazards inherent in the surface soil of Chenzhou City. A comprehensive analysis was conducted on 600 systematically collected soil samples within the study area, utilizing enrichment factors, geo-accumulation indices, comprehensive pollution indices, potential ecological hazard indices, and health risk assessment models to evaluate the degree of heavy metal contamination in the soil, potential ecological risks, and associated health hazards. The findings reveal that the average enrichment factor (EF) for each heavy metal is below 2, with the hierarchy from highest to lowest being Hg > Cd > Cu > Pb > Ni > Zn > Cr > As. Approximately 78.67% of soil samples exhibit no pollution to weak pollution levels based on heavy metal enrichment factors. Moreover, the comprehensive pollution index (IPIN) indicates that 95.17% of soil samples are within safe and pollution-free levels, indicating an overall environmentally secure setting. However, 2.67% of samples display heightened potential ecological risk levels, primarily concentrated in the southwestern region of the study area, influenced by nearby industrial activities. Additionally, it is noteworthy that both the non-carcinogenic and carcinogenic health hazards emanating from soil heavy metals to adult individuals lie within tolerable thresholds. Among these, arsenic (As), chromium (Cr), and lead (Pb) have been discerned as the principal non-carcinogenic agents. It is of particular significance that only a solitary soil specimen, located in the southwestern quadrant of the investigative region, manifests detectable health perils for children.

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Section: Literature Reviewmentioning

confidence: 99%

Characteristics of Soil Heavy Metal Pollution and Health Risks in Chenzhou City

Kuang,

Chen,

Zhu

2024

Processes

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“…Información sobre distribución espacial y las posibles fuentes de contaminación por metales pesados en tierras agrícolas es muy importante para la salud humana y la seguridad alimentaria. Debido a eso, Günal et al (2023) evaluaron el grado de contaminación por plomo (Pb), cadmio (Cd) y níquel (Ni) en la parte sureste de Turquía, mediante el índice de geoacumulación (Igeo), el factor de contaminación modificado (mCdeg) y el índice de contaminación de Nemerow (PINemerow), los cuales fueron combinados con autocorrelación espacial utilizando algoritmos de aprendizaje profundo.…”

Section: Sistemas De Inteligencia Artificial Para La Agriculturaunclassified

Inteligencia artificial en agricultura - Uso de algoritmos, drones y biosensores

Lira-Saldivar,

Lara-Viveros

2023

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Editora Direitos para esta edição cedidos à Atena Editora pelos autores. Open access publication by Atena Editora Todo o conteúdo deste livro está licenciado sob uma Licença de Atribuição Creative Commons. Atribuição-Não-Comercial-NãoDerivativos 4.0 Internacional (CC BY-NC-ND 4.0). O conteúdo do texto e seus dados em sua forma, correção e confiabilidade são de responsabilidade exclusiva dos autores, inclusive não representam necessariamente a posição oficial da Atena Editora. Permitido o download da obra e o compartilhamento desde que sejam atribuídos créditos aos autores, mas sem a possibilidade de alterála de nenhuma forma ou utilizá-la para fins comerciais.Todos os manuscritos foram previamente submetidos à avaliação cega pelos pares, membros do Conselho Editorial desta Editora, tendo sido aprovados para a publicação com base em critérios de neutralidade e imparcialidade acadêmica.A Atena Editora é comprometida em garantir a integridade editorial em todas as etapas do processo de publicação, evitando plágio, dados ou resultados fraudulentos e impedindo que interesses financeiros comprometam os padrões éticos da publicação. Situações suspeitas de má conduta científica serão investigadas sob o mais alto padrão de rigor acadêmico e ético. Conselho Editorial Ciências Agrárias e Multidisciplinar

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A Systematic Review of the Outcomes of Utilization of Artificial Intelligence Within the Healthcare Systems of the Middle East: A Thematic Analysis of Findings

Khosravi,

Mojtabaeian,

Demiray

et al. 2024

Health Science Reports

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Background and AimsThe rapid expansion of artificial intelligence (AI) within worldwide healthcare systems is occurring at a significant rate. In this context, the Middle East has demonstrated distinctive characteristics in the application of AI within the healthcare sector, particularly shaped by regional policies. This study examined the outcomes resulting from the utilization of AI within healthcare systems in the Middle East.MethodsA systematic review was conducted across several databases, including PubMed, Scopus, ProQuest, and the Cochrane Database of Systematic Reviews in 2024. The quality assessment of the included studies was conducted using the Authority, Accuracy, Coverage, Objectivity, Date, Significance checklist. Following this, a thematic analysis was carried out on the acquired data, adhering to the Boyatzis approach.Results100 papers were included. The quality and bias risk of the included studies were delineated to be within an acceptable range. Multiple themes were derived from the thematic analysis including: “Prediction of diseases, their diagnosis, and outcomes,” “Prediction of organizational issues and attributes,” “Prediction of mental health issues and attributes,” “Prediction of polypharmacy and emotional analysis of texts,” “Prediction of climate change issues and attributes,” and “Prediction and identification of success and satisfaction among healthcare individuals.”ConclusionThe findings emphasized AI's significant potential in addressing prevalent healthcare challenges in the Middle East, such as cancer, diabetes, and climate change. AI has the potential to overhaul the healthcare systems. The findings also highlighted the need for policymakers and administrators to develop a concrete plan to effectively integrate AI into healthcare systems.

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Combining spatial autocorrelation with artificial intelligence models to estimate spatial distribution and risks of heavy metal pollution in agricultural soils

Cited by 8 publications

References 85 publications

Characteristics of Soil Heavy Metal Pollution and Health Risks in Chenzhou City

Characteristics of Soil Heavy Metal Pollution and Health Risks in Chenzhou City

Inteligencia artificial en agricultura - Uso de algoritmos, drones y biosensores

A Systematic Review of the Outcomes of Utilization of Artificial Intelligence Within the Healthcare Systems of the Middle East: A Thematic Analysis of Findings

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