Antibiotic Resistance

Antibiotic resistance, a critical global health threat, necessitates research focused on improving prediction and treatment strategies. Current research employs machine learning, particularly deep neural networks (like recurrent neural networks and convolutional neural networks) and natural language processing models, analyzing diverse data sources including electronic health records and genomic sequences to predict resistance, identify risk factors, and optimize antibiotic stewardship. These efforts aim to enhance diagnostic accuracy, personalize treatment, and ultimately reduce morbidity and mortality associated with resistant infections, impacting both clinical practice and public health initiatives.