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Article ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 2 ? Original research — experimental, observational, or case-control study. Direct primary evidence. Detection Methods Human Health Effects Marine & Wildlife Sign in to save

Detection of Microplastic Ingestion in the Human Body Using Deep Learning Technique

2024 1 citation ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count.
Hari Chandana B, Chandana Challa, A. G., Guru Murthy T, T Diwakar

Summary

Researchers applied convolutional neural networks trained in MATLAB to detect and quantify microplastic contamination in high-resolution tissue images, demonstrating that deep learning can automate the identification of plastic particles in biological samples.

Body Systems
Nervous

This study investigates using Neural Networks with convolution(CNNs) MATLAB to detect microplastic contamination in human tissues. As microplastics threaten health and ecosystems, this study provides a CNN-based method for their precise identification and quantification in high-resolution tissue images. This approach includes image preprocessing and CNN optimization to detect microplastic characteristics accurately. The effectiveness of model is confirmed through key performance metrics. Results advance deep learning in environmental health and aid in understanding and preventing microplastic-related health risks.

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