AIMC Topic: Machine Learning

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Integrating machine learning and reliability analysis: A novel approach to predicting heavy metal removal efficiency using biochar.

Ecotoxicology and environmental safety
Soil contamination with heavy metals (HMs) presents critical environmental and public health risks due to their long-term persistence and tendency to bioaccumulate. Biochar has gained recognition as an effective amendment for HM immobilization, owing...

Trends and advances in image-based mosquito identification and classification using machine learning models: A systematic review.

Computers in biology and medicine
Mosquito-borne diseases, such as Yellow fever, Dengue, and Zika, pose a significant global health threat, causing millions of deaths annually. Traditional mosquito identification methods, reliant on expert analysis, are time-consuming and resource-in...

The impact of socio-economic factors on the ecological footprint in Turkey: A comprehensive analysis using machine learning approaches.

Journal of environmental management
This study undertakes a comprehensive investigation into the impact of socioeconomic factors on the ecological footprint (EFP) in Turkey. It employs robust econometric methods and advanced Machine Learning (ML) models. The study employs Generalized L...

A high-resolution GIS and machine learning approach for targeted disease management and localized risk assessment in an urban setup: A case study from Bhopal, Central India.

Acta tropica
Predicting dengue distribution based on environmental factors is crucial for effective vector control and management as environmental factors like temperature, demographics, and artificial changes such as roads and buildings significantly influence d...

Development and validation of an interpretable machine learning model for predicting hyperuricemia risk: Based on environmental chemical exposure.

Ecotoxicology and environmental safety
Hyperuricemia is a global health concern, with environmental chemicals as risk factors. This study used data of multiple environmental chemical exposures from the 2011-2012 cycle of the National Health and Nutrition Examination Survey (NHANES) to dev...

Revealing the impacts of the built environment factors on pedestrian-weighted air pollutant concentration using automated and interpretable machine learning.

Journal of environmental management
Urban air pollution poses significant health risks, especially to pedestrians due to their proximity to pollutants and lack of physical protection. Understanding the influence of built environment factors is essential to mitigate this pollution and s...

A cluster attention-based multiple instance learning network for enhancing histopathological image interpretation.

Computers in biology and medicine
BACKGROUND: Histopathological diagnosis involves examining abnormal architectural patterns and cellular-level changes. Whole slide images (WSIs) provide comprehensive digital representations of tissue samples, enabling detailed analysis and interpret...

A machine learning framework for cross-institute standardized analysis of flow cytometry in differentiating acute myeloid leukemia from non-neoplastic conditions.

Computers in biology and medicine
Flow cytometry (FC) remains a cornerstone diagnostic tool for acute myeloid leukemia (AML), yet standardizing panels across laboratories presents persistent challenges. Our study introduces a validated machine learning framework enabling cross-panel ...

Machine learning-driven nanoparticle toxicity.

Ecotoxicology and environmental safety
This study presents a comprehensive machine learning-driven analysis to understand and predict the toxicity of nanoparticles (NPs), a crucial aspect in ensuring the safe application of nanotechnology in medicine, pharmaceuticals, biotechnology, and v...

Long-term water quality simulation and driving factors identification within the watershed scale using machine learning.

Journal of contaminant hydrology
Understanding long-term trends and analyzing their driving factors are essential to effectively enhance water quality in watersheds. In China, although the overall quality of surface water continues to improve, significant issues remain in certain re...