Anna is a Senior Scientist in the Genetics and Genome Biology Program at SickKids Research Institute and Associate Professor in the Department of Computer Science at the University of Toronto (Computational Biology Group) with a cross appointment in the department of Statistics. Her main research focus is to develop machine learning methods that can help decipher human disease heterogeneity, which involves combining data from multiple sources. Examples of her recent research include predicting necessity of thyroid biopsy and resection and age of cancer onset in children with cancer predisposition syndrome. Anna trained in machine learning at Carnegie Mellon University, with a postdoctoral focus in computational biology. The Goldenberg Lab collaborates with clinicians to ensure that work is relevant in the clinic. Anna is also a Member of the CIFAR Child and Brain Development group and a Member of the Scientific Management Committee of the Centre for Computational Medicine at SickKids.
Associate Professor, Department of Computer Science, Faculty of Arts & Science, University of Toronto
Associate Research Director- Health, Vector Institute
Canada CIFAR Artificial Intelligence Chair
Senior Scientist, SickKids
Varma Family Chair of Medical Bioinformatics and Artificial Intelligence
Research Interests
- Computational biology
Highlights
- Department of Computer Science Award for exceptional mentoring and outstanding commitment to graduate student recruitment, University of Toronto
- Early Researcher Award from the Ministry of Research and Innovation
Publications
How interpretable and trustworthy are gams?
2021
A Research Ethics Framework for the Clinical Translation of Healthcare Machine Learning
2022
A comprehensive EHR timeseries pre-training benchmark
2021
Development and validation of an ensemble machine learning framework for detection of all-cause advanced hepatic fibrosis: a retrospective cohort study
2022
Postnatal developmental trajectory of sex-biased gene expression in the mouse pituitary gland
2022
An Alternative to the Light Touch Digital Health Remote Study: The Stress and Recovery in Frontline COVID-19 Health Care Workers Study
2021
Predicting Malignancy in Pediatric Thyroid Nodules: Early Experience With Machine Learning for Clinical Decision Support
2021
Finding associations in a heterogeneous setting: statistical test for aberration enrichment
2021
Assessing therapy response in patient-derived xenografts
2021
MP44-18 accurate estimate of split differential renal function using ultrasound alone for infants with hydronephrosis
2021
Standardized Reporting of Machine Learning Applications in Urology: The STREAM-URO Framework
2021
Dear watch, should I get a COVID test? designing deployable machine learning for wearables
2021
Better Understanding of the Metamorphosis of Pregnancy (BUMP): protocol for a digital feasibility study in women from preconception to postpartum
2022
Assessment of Machine Learning–Based Medical Directives to Expedite Care in Pediatric Emergency Medicine
2022
Identification of Optical Coherence Tomography Phenotypes and Their Relationship with Patient Outcomes in Youth With Demyelinating Syndromes: Preliminary Results of an Unsupervised Machine Learning Analysis
2021