The Research Progress of Machine Learning Applications in the Field of Antibiotic Contamination
Antibiotics and their degradation products,once they entered ecosystems,were capable of inducing the production and spread of antibiotic resistance genes,severely impacting the stability and functionality of ecosystems.Therefore,the rapid and systematic detection and removal of antibiotics were crucial for maintaining ecological balance and human health.With the development of computer science,especially artificial intelligence technologies,machine learning algorithms had been widely applied in the field of antibiotic pollution research.Research indicated that machine learning algorithms,compared to traditional methods,demonstrated higher efficiency and accuracy in the detection of antibiotic pollution,analysis of the origins of resistance genes,and the assessment of degradation effects.Consequently,the application of machine learning algorithms in the field of antibiotic pollution control was expected to reveal substantial potential and practical value in the future.
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