Prof Enes Makalic
Honorary (Professorial Fellow)
Melbourne School of Population and Global Health
337 Scholarly works
17 Projects
HIGHLIGHTS
2026
Journal article
AutoCumulus: an automated mammographic density measure created using artificial intelligence
DOI: 10.1186/s12885-026-16264-z2026
Journal article
Extremely Fast Maximum Likelihood Estimation of High-Order Autoregressive Models
DOI: 10.1111/jtsa.128392026
Journal article
Tumour-based DNA methylation markers of breast cancer survival: a pooled analysis of 2157 cases.
DOI: 10.1186/s13058-026-02327-32024
Research grants (ARC, NHMRC, MRFF)
Centre of Research Excellence and Expertise in Genetic Epidemiology for Precision Population Health
2023
Journal article
Australian genome-wide association study confirms higher female risk for adult glioma associated with variants in the region of CCDC26
DOI: 10.1093/neuonc/noac2792021
Research grants (ARC, NHMRC, MRFF)
Centre of Research Excellence in Precision Public Health Approaches to Breast Cancer Screening, Early Detection and Mortality Reduction
2018
Research Grant
Improved and Automated Measures of Breast Cancer Risk Based on Digital Mammography and Family History Data Collected by Breastscreen That Will Enable Tailored Screening for Breast Cancer
RECENT SCHOLARLY WORKS
2026
Journal article
Information Geometry and Asymptotic Theory for SMML Estimators
DOI: 10.3390/e280607132026
Journal article
AI-based BRAIx risk score for the intermediate-term prediction of breast cancer: a population cohort study
DOI: 10.1016/j.landig.2026.1009872026
Other
Supplementary Table S2 from Region-Based Analyses of Existing Genome-Wide Association Studies Identifies Novel Potential Genetic Susceptibility Regions for Glioma
DOI: 10.1158/2767-9764.317622672026
Other
Supplementary Table S9 from Region-Based Analyses of Existing Genome-Wide Association Studies Identifies Novel Potential Genetic Susceptibility Regions for Glioma
DOI: 10.1158/2767-9764.317622402026
Other
Supplementary Table S5 from Region-Based Analyses of Existing Genome-Wide Association Studies Identifies Novel Potential Genetic Susceptibility Regions for Glioma
DOI: 10.1158/2767-9764.317622522026
Other
Data from Region-Based Analyses of Existing Genome-Wide Association Studies Identifies Novel Potential Genetic Susceptibility Regions for Glioma
DOI: 10.1158/2767-9764.c.75353162026
Other
Supplementary Figure S2 from Region-Based Analyses of Existing Genome-Wide Association Studies Identifies Novel Potential Genetic Susceptibility Regions for Glioma
DOI: 10.1158/2767-9764.31762276
RECENT PROJECTS
2024
Research contracts (non-grants)
Using Machine Learning to Improve Polygenic Risk Prediction of Cancer