11th Edition of World Congress on Infectious Diseases
June 28-30, 2027 | Rome, Italy
Artificial Intelligence and Big Data in Infectious Disease Management
Artificial intelligence (AI) and big data are revolutionizing infectious disease management by enhancing the speed and accuracy of diagnosis, treatment, and outbreak prediction. Through the application of artificial intelligence and big data in infectious disease management, AI algorithms are used to analyze vast amounts of data, such as patient records, genetic sequences, and epidemiological trends, to identify patterns and predict potential outbreaks. Big data allows healthcare systems to make informed decisions based on real-time information, improving resource allocation and response times. By leveraging machine learning models, healthcare providers can personalize treatment plans and detect infections earlier, leading to better patient outcomes. The integration of AI and big data is essential for creating more efficient, proactive approaches to managing infectious diseases globally.
Ranjan Ramasamy
ID-FISH Technology, United States
Yazdan Mirzanejad
University of British Columbia, Canada
Elena Chiappini
University of Florence, Italy
Saurabh Chattopadhyay
University of Kentucky College of Medicine, United States
Sergey Suchkov
N.D. Zelinskii Institute for Organic Chemistry of the Russian Academy of Sciences & InMedStar, Russian Federation
Masafumi Seki
Saitama Medical University International Medical Center, Japan
Martha Grace McLean
Anne Burnett Marion School of Medicine at Texas Christian University, United StatesSubmit your abstract Today
Title : Diagnostic approaches, predictive and prognostic assessments, monitoring, treatment & management of infectious diseases and disease prevention
Sergey Suchkov, N.D. Zelinskii Institute for Organic Chemistry of the Russian Academy of Sciences & InMedStar, Russian Federation
Title : The accelerated timeline: Human ecology, climate change, and the next global outbreak
Claudia Ferreira, Sorbonne University, France
Title : Climate change and increasing death due to resistant infection
Yazdan Mirzanejad, University of British Columbia, Canada
Title : Recurrent klebsiella pneumoniae pyogenic liver abscess: Developing a literature-informed 0–2 scoring framework from a solved index case
Martha Grace McLean, Anne Burnett Marion School of Medicine at Texas Christian University, United States
Title : Post-hysterectomy pelvic abscess mimic: An AI-assisted diagnostic stewardship workflow
Setu Shiroya, Anne Burnett Marion School of Medicine at Texas Christian University, United States
Title : Building a clinical reasoning tool from post-transplant MRSA sepsis: A mentored ai workflow
Michaela Mitchell, Anne Burnett Marion School of Medicine at Texas Christian University, United States