Medicine and Healthnpj Antimicrobials & Resistance
Interpretable machine learning-based decision support for prediction of antibiotic resistance for complicated urinary tract infections
J. Yang, D. W. Eyre, et al.
Discover how a collaborative team of researchers, including Jenny Yang and David W. Eyre, has developed innovative machine learning algorithms that predict antibiotic resistance in urinary tract infections. Their work not only enhances treatment efficacy but also promotes personalized care through interpretability in model design.
Related Publications
Explore these studies to deepen your understanding
Adjacent work that informs or extends this paper's methodology and findings.
Medicine and Health
Machine learning based suicide prediction and development of suicide vulnerability index for US counties
V. Kumar, K. K. Sznajder, et al.
Medicine and Health
Machine learning-based prediction of in-hospital death for patients with takotsubo syndrome: The InterTAK-ML model
O. D. Filippo, V. L. Cammann, et al.
Medicine and Health
Prediction of mortality risk and duration of hospitalization of COVID-19 patients with chronic comorbidities based on machine learning algorithms
P. Amiri, M. Montazeri, et al.
Medicine and Health
Machine learning-based prediction of COVID-19 diagnosis based on symptoms
Y. Zoabi, S. Deri-rozov, et al.
