• The complexities of biofilm: novel applications of artificial intelligence in microbial identification and control
  • Amirhossein Khorramian,1,* Sara Sojoodi korabbaslou,2 Arezoo Hashemi khademlou,3 Hannaneh Amadeh,4
    1. Department of Microbiology,La.C., Islamic Azad University, Lahijan , Iran
    2. Department of Microbiology, Faculty of Basic Sciences, Islamic Azad University, Ardabil Branch, Ardabil, Iran
    3. Department of Microbiology, Faculty of Basic Sciences, Islamic Azad University, Ardabil Branch, Ardabil, Iran
    4. Department of Microbiology, Faculty of Basic Sciences, Islamic Azad University, Ardabil Branch, Ardabil, Iran


  • Introduction: Biofilms are complex communities of microbes that adhere to surfaces and pose many problems in the fields of medicine, environment, and industry due to their high resistance to conventional treatment methods. Accurate identification and analysis of biofilms is of great importance for their effective management. In recent years, artificial intelligence (AI) has entered the biofilm research field as a transformative tool and has contributed greatly to this field with advanced capabilities such as big data analysis and accurate pattern recognition.
  • Methods: This review article examines various AI-based methods, including machine learning and deep learning, that have been used for biofilm identification. The types of data used in these studies, such as images, genetic data, and biochemical markers, are examined. AI algorithms enable early detection, classification, and monitoring of biofilms with greater accuracy, overcoming the limitations of traditional methods that struggled to analyze complex and variable biofilm data.
  • Results: In addition to technical advances, challenges such as data quality, model interpretation, and the need to develop standardization protocols are also discussed.
  • Conclusion: Finally, future directions in this field include integrating AI technologies into biofilm control strategies and improving application outcomes in various fields. Overall, AI offers a promising prospect for overcoming the limitations of biofilm detection and analysis, and plays an important role in scientific and practical advances in microbiology
  • Keywords: Biofilm - microbial identification - artificial intelligence