Wallace Pereira
Papers
1
Total Citations
9
H-Index
1
About
Wallace Pereira is a researcher whose work sits at the intersection of nephrology and machine learning, with a particular focus on improving outcomes for elderly kidney transplant recipients. His most cited paper, "Logistic Regression Model in a Machine Learning Application to Predict Elderly Kidney Transplant Recipients with Worse Renal Function One Year after Kidney Transplant: Elderly KTbot" (2020, 9 citations), introduces a predictive model that leverages logistic regression to identify elderly patients at risk of poor renal function post-transplant. This contribution is significant because it addresses the growing challenge of renal replacement therapy as a public health issue, offering a data-driven tool to personalize care for an aging population. By comparing elderly versus younger recipients, Pereira's work highlights the nuanced risk factors that affect graft survival and patient longevity. His research demonstrates a practical application of machine learning in clinical decision-making, aiming to enhance the quality of life for elderly patients undergoing kidney transplantation. With a focus on translational impact, Pereira's findings are valuable for nephrologists and data scientists seeking to integrate predictive analytics into transplant medicine.
Research Focus
Key Achievements
Top Papers
- 1