AI-Driven Hyperspectral Morphotoxic Profiling of Opportunistic Pathogens in Mixed Biofilm Contaminations
Abstract
The health care, environmental, and industrial infrastructures encounter challenging issues when dealing with biofilm forming opportunistic pathogens because of their persistence, antimicrobial resistance, and the capacity to coexist in a complex mixed microbial composition. Fast and non-invasion methods of detecting microbial content in biofilms are hence key towards successful monitoring and control. This paper suggests a hyperspectral morphotoxic profiling workflow that uses artificial intelligence and is applicable to analyzing mixed biofilm contaminations of opportunistic pathogens. The method combines hyperspectral imaging and artificial intelligence to identify and make sense of spectral-morphological features of microbial biofilms. The first stage entails the hyperspectral image data acquisition and preprocessing to eliminate noise and standardize spectral content, and the second stage is the dimensionality reduction to retain the most informative spectral data and reduce the complexity of the data. They then train a convolutional neural network to be able to learn discriminative spatial and spectral patterns related to the structures of microbial biofilms and presence of the pathogen in the processed images. The trained model is tested on the basis of automatic delivery of microbial signatures in intricate biofilm settings. To ensure ease of application and illustrate practicality, a simple web based interface will be built with flask framework where one will be able to upload images and get instant AI based predictions through an interactive solution. The current framework of hyperspectral imaging, artificial intelligence, and web-based implementation with a focus on microbial profiling in only a few seconds is discussed as a potential option, and hyperspectral imaging could be used in the context of environmental toxicology, monitoring infections, water quality assessment, and managing biofilm in industries.
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