Katarzya Lamparska
Papers
1
Total Citations
6
H-Index
1
About
Katarzyna Lamparska has made significant contributions to the field of oncological diagnostics, with a primary focus on improving the prediction of prostate cancer outcomes. Her research centers on the development and application of advanced statistical and machine learning methods, particularly two-stage classifiers, to enhance the accuracy of prognostic models. In her most cited work, she pioneered a novel approach that integrates PCA3 testing with PSA proteolytic activity measurements to predict biochemical recurrence after radical prostatectomy. This study, published in 2017, demonstrated how combining these biomarkers can refine risk stratification for patients, addressing the critical clinical need to identify early recurrence—a hallmark of aggressive disease. While her citation count of 6 reflects a specialized but impactful contribution, Lamparska’s work stands out for its methodological rigor and translational potential, offering a pathway toward more personalized post-surgical monitoring. Her achievements underscore a commitment to bridging computational modeling and clinical oncology, making her a notable figure in the advancement of precision medicine for prostate cancer management.
Research Focus
Key Achievements
Top Papers
- 1