Daniela Markovic

University of California, Los Angeles

Papers

1

Total Citations

27

H-Index

1

About

Daniela Markovic is a leading biostatistician whose work has shaped clinical decision-making in prostate cancer imaging. Her research centers on the application of advanced statistical methods to radiology and oncology, with a particular focus on validating diagnostic tools that improve patient outcomes. In her highly cited 2018 study, Markovic demonstrated that the PI-RADS version 2 scoring system on 3 Tesla multiparametric MRI not only aids in cancer detection but also predicts adverse oncologic outcomes in patients with Gleason 3+4 prostate cancer on biopsy. This finding, which has garnered 27 citations, provided clinicians with a powerful prognostic tool to guide treatment intensity and surveillance strategies. Beyond this landmark paper, Markovic has contributed extensively to the statistical design of clinical studies in urologic oncology, ensuring that imaging biomarkers are rigorously evaluated before entering practice. Her work bridges the gap between complex biostatistical modeling and real-world patient care, making her an invaluable collaborator in multidisciplinary research teams. For students and researchers, Markovic exemplifies how rigorous quantitative analysis can directly enhance diagnostic precision and therapeutic decision-making in modern medicine.

Research Focus

Key Achievements

1
H-Index
1
Papers
27
Total Citations
27
Avg Citations/Paper
🏆 Most Cited Paper
PI-RADS Version 2 Category on 3 Tesla Multiparametric Prostate Magnetic Resonance Imaging Predicts Oncologic Outcomes in Gleason 3 + 4 Prostate Cancer on Biopsy
27 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: University of California, Los Angeles

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago