AI-Driven Bacterial Identification: A Hybrid Deep Learning and Machine Learning Framework

This work applies Deep Learning(DL) and Machine Learning(ML) to automate and enhance bacterial identification from medical images, addressing the limitations of traditional culture-based and biochemical methods, which are slow and labor-intensive. In the medical industry, rapid and accurate bacterial classification is crucial for timely diagnosis and effective treatment, particularly in the face of rising antimicrobial resistance. By improving efficiency and reducing manual effort, This method offers substantial benefits. for clinical microbiology, aiding in faster pathogen identification and personalized treatment strategies. Future advancements may enable real-time diagnostics and integration with electronic health records, enhancing precision medicine and hospital infection control efforts.