معرفی
Mikael Eriksson is an Assistant Professor in the Department of Medical Epidemiology and Biostatistics at Karolinska Institutet, Sweden, where he leads research in breast cancer epidemiology as part of Kamila Czene's research group. His work focuses on developing individualized risk assessment techniques to optimize mammography screening programs and reduce breast cancer mortality.
Eriksson specializes in identifying women who have suboptimal benefit from standard screening protocols, including those who may need additional screening resources and those who may not benefit at all from mammography screening. His research spans multiple areas including long-term risk modeling, prophylactic therapies, risk-reducing treatments, and addressing masking in mammography screening caused by dense breast tissue. Using advanced epidemiological methods and AI-based approaches, his work bridges population health with personalized medicine approaches to breast cancer prevention.
Eriksson's publication record demonstrates a strong focus on translating research into clinical applications, with numerous studies examining mammographic density, genetic risk factors, and AI-based risk prediction models. His work frequently appears in high-impact journals including JAMA Oncology, Breast Cancer Research, and the Journal of the National Cancer Institute, showing consistent contributions to understanding breast cancer risk factors and improving screening methodologies.
He has received significant recognition including the European Commission Marie Curie 4-year grant (totaling 4.7 million Euro) for establishing a European doctoral network with institutions including Cambridge University, Oxford University, and others across Europe. Eriksson also represents Karolinska Institutet in the Cancer Prevention Europe (CPE) Early Career Network.
His current research program includes multiple funded projects examining risk assessment and prevention of breast cancer, including a randomized double-blind phase II trial comparing baby tamoxifen versus baby exemestane in post-menopausal women at high risk for breast cancer (BabyTEARS), and AI image-based model development for long-term breast cancer risk assessment in Swedish and U.S. screening settings.
