Biruk Tsegaye
Medical Statistician
I’m a medical statistician interested in clinical prediction studies (prognosis and diagnosis) using different machine learning algorithms in healthcare, particularly in oncology.
I joined NDORMS in December 2022 as a medical statistician, since then I have been working with different systematic reviews mainly on sample size calculations for prediction model also I am working with Perioperative Quality Improvement Programme (PQIP) that mainly aimed at quality improvement initiative to improve care along perioperative pathways for the real benefit of patients by helping clinicians in using data to improve patients outcome, minimize differences in processes of care and supporting implementation of best practice.
Academically I have mixed background: MSc in medical statistics, MSc in Biomedicine and undergraduate in Doctor of Veterinary Medicine (DVM).
Recent publications
Substantial international variation in the cost of blood group and save and crossmatch: A systematic review.
Journal article
Fabiano G. et al, (2026), Br J Haematol
Larger sample sizes are needed when developing a clinical prediction model using machine learning in oncology: methodological systematic review.
Journal article
Tsegaye B. et al, (2025), J Clin Epidemiol, 180
Clinical prediction models using machine learning in oncology: challenges and recommendations.
Journal article
Collins GS. et al, (2025), BMJ Oncol, 4