- Mammographic density and cancer risk
- Online research methods course: building research literacy
- Pubilc health surveillance systems: breast screening
- Mammographic density and breast cancer risk
- Open source electronic medical records
- Modelling clinical outcomes, incorporating both diagnostic image features and clinical factors
- Clinical decision support tools employing SPC and statistical learning algorithms
- Online research methods curriculum for medical residents and research in education
- Public health informatics
- Reproducible research adhering to literate statistical programming principles
- Translation of academic research to industry
- Associate professor, Department of Diagnostic Radiology, Dalhousie Medical School
- Affiliated scientist, QEII Health Sciences Centre
- MSc, (Biostatistics), University of Toronto
- BSc, (Applied Mathematics and Statistics), University of Toronto
Mo Abdolell is a biostatistician who, through the application of statistical models, develops solutions to help clinicians make evidence-based decisions relating to diagnosis and treatment of patients. Appropriateness of care, namely the appropriate use of technologies from both the healthcare system efficiency and patient outcomes perspectives, is the ultimate goal.
Professor Abdolell mines, analyzes and models data generated through the Nova Scotia Breast Screening Program that is linked to image data from the diagnostic imaging department to help create and improve clinical decision-making tools for breast cancer screening. With his work in this area, Professor Abdolell wants to improve early detection of breast cancer. This is also the overarching theme of his other research foci, which include understanding how breast density affects the application of mammography, and translational research to ensure his research has an immediate and direct impact on patient care.
“Breast density affects the accuracy of mammography and women with dense breast tissue are at greater risk of breast cancer, so there is a heightened urgency for research in this area. There is also the opportunity to contribute greatly to our knowledge of breast cancer and to patient outcomes,” says Professor Abdolell.
His interest in breast density has led to the establishment of an early stage medical device software Denitas Inc. which develops digital mammography products addressing the clinical and administrative requirements of hospitals and radiology clinics.
The company develops data-driven solutions for clinical decision making, leveraging their extensive expertise in the data sciences, encompassing the fields of biostatistics, epidemiology, health informatics, medical imaging and embedded algorithms in the diagnostic imaging space.
Breast Density research is a major focus of the Section with collaboration with other breast imagers from Nova Scotia and PEI; multiple abstracts have been presented at the European Congress of Radiology and we have recently published "Consistency of visual assessments of mammographic breast density from vendor-specific 'for presentation' images in the Journal of Medical Imaging."