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.
Title : Extensively drug-resistant bacterial infections: Confronting a global crisis with urgent solutions in prevention, surveillance, and treatment
Yazdan Mirzanejad, University of British Columbia, Canada
Title : Pathogen-derived noncanonical epitopes: Are they valuable targets for novel vaccinations and shall we be concerned about autoimmune responses?
Michele Mishto, Francis Crick Institute, United Kingdom
Title : Bioterrorism through the ages: Historical perspective, emerging threats, and medical countermeasures
Claudia Ferreira, Sorbonne University, France
Title : A rare case of meningitis and septicemia due to Streptococcus acidominimus
Percival C Dilla, Region II Trauma and Medical Center, Philippines
Title : Measles vaccination coverage indicators in 2023 and advance towards measles elimination and eradication by 2030
Pedro Plans Rubio, College of Physicians of Barcelona, Spain
Title : Association between cardiometabolic risk factors and COVID-19 severity in patients of a rural tertiary hospital
Percival C Dilla, Region II Trauma and Medical Center, Philippines