Clinical laboratories have been playing a pivotal role in understanding biology, disease and molecular medicine. Approximately 70% of the decisions regarding a patient’s diagnosis and treatment are based on laboratory results.
Clinical Microbiology Laboratories have been relying on conventional diagnostic methods. Automation of clinical laboratories has transformed the departments of Biochemistry and Pathology in a significant way. Yet, Clinical Microbiology laboratories must have the technology to replace the existing conventional cultural methods. Clinical and microbiological diagnostics have made technological improvements, yet they are expensive to reach medium microbiology facilities. In the wake of Artificial Intelligence making a path into the diagnostics, as evidenced by the image-based diagnostics in Radiology and Pathology, Can Artificial intelligence provide solutions to clinical and microbiological laboratories?
Clinical microbiology laboratories are the first line of defence in the fight against infectious illnesses and antibiotic resistance, particularly recently emerged. Although most clinical laboratories currently use traditional methods, technological advancements fueled by digital imaging and high-throughput sequencing will transform clinical diagnostics management for direct bacteria identification and rapid antibiotic susceptibility testing. Notably, such technical developments occur during the golden age of machine learning, when computers are no longer just passive data miners but can also assist clinicians in making diagnostic and treatment decisions once they have been adequately educated. This presentation will navigate through the applications of the Artificial intelligence and Machine learning in the Diagnostic Microbiology Laboratories and Discuss such technological advancements by providing practical instances of their use, as well as their limitations and potential challenges that their use in clinical microbiology laboratories could cause.
What will audience learn from your presentation?
- Audience will learn about Definitions of Artificial intelligence and Machine learning.
- Will be able to know the current advancements in the field of clinical microbiology diagnostic by incorporating Artificial intelligence and Machine learning.
- This knowledge will help them to take forward the implementation of artificial intelligence in the clinical diagnostics and also critically think about the limitations of the technology incorporation in routine diagnostics.
- They can form new solutions and come up with new technological solutions for diagnostic which can be economical.