Anna Goldenberg
Orcid: 0000-0002-2416-833XAffiliations:
- University of Toronto, ON, Canada
According to our database1,
Anna Goldenberg
authored at least 70 papers
between 2001 and 2024.
Collaborative distances:
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Bibliography
2024
CoRR, 2024
Integrate Any Omics: Towards genome-wide data integration for patient stratification.
CoRR, 2024
2023
Proceedings of the 19th International Symposium on Medical Information Processing and Analysis, 2023
Proceedings of the Machine Learning for Health, 2023
What's fair is... fair? Presenting JustEFAB, an ethical framework for operationalizing medical ethics and social justice in the integration of clinical machine learning: JustEFAB.
Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023
Proceedings of the Workshop on Data Science Techniques for Datasets on Mental and Neurodegenerative Disorders co-located with SDS23 IEEE Swiss Conference on Data Science(IEEESDS'23), 2023
2022
npj Digit. Medicine, 2022
Better Understanding of the Metamorphosis of Pregnancy (BUMP): protocol for a digital feasibility study in women from preconception to postpartum.
npj Digit. Medicine, 2022
Frontiers Digit. Health, 2022
Frontiers Digit. Health, 2022
From Single-Visit to Multi-Visit Image-Based Models: Single-Visit Models are Enough to Predict Obstructive Hydronephrosis.
CoRR, 2022
CoRR, 2022
CoRR, 2022
Proceedings of the Machine Learning for Healthcare Conference, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Volume-based Performance not Guaranteed by Promising Patch-based Results in Medical Imaging.
Proceedings of the Proceedings on "I Can't Believe It's Not Better!, 2022
Proceedings of the Conference on Health, Inference, and Learning, 2022
How to validate Machine Learning Models Prior to Deployment: Silent trial protocol for evaluation of real-time models at ICU.
Proceedings of the Conference on Health, Inference, and Learning, 2022
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
2021
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021
Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding.
Proceedings of the 9th International Conference on Learning Representations, 2021
Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021
Proceedings of the ACM CHIL '21: ACM Conference on Health, 2021
2020
Patient safety and quality improvement: Ethical principles for a regulatory approach to bias in healthcare machine learning.
J. Am. Medical Informatics Assoc., 2020
CoRR, 2020
A Comprehensive Evaluation of Multi-task Learning and Multi-task Pre-training on EHR Time-series Data.
CoRR, 2020
CoRR, 2020
What went wrong and when? Instance-wise feature importance for time-series black-box models.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Machine Learning for Healthcare Conference, 2020
Hidden Risks of Machine Learning Applied to Healthcare: Unintended Feedback Loops Between Models and Future Data Causing Model Degradation.
Proceedings of the Machine Learning for Healthcare Conference, 2020
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
2019
Machine learning for integrating data in biology and medicine: Principles, practice, and opportunities.
Inf. Fusion, 2019
CoRR, 2019
Dr.VAE: improving drug response prediction via modeling of drug perturbation effects.
Bioinform., 2019
What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use.
Proceedings of the Machine Learning for Healthcare Conference, 2019
Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks.
Proceedings of the Machine Learning for Healthcare Conference, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
Proceedings of the 7th International Conference on Learning Representations, 2019
2018
CoRR, 2018
Rethinking clinical prediction: Why machine learning must consider year of care and feature aggregation.
CoRR, 2018
CoRR, 2018
CoRR, 2018
Proceedings of the Machine Learning for Healthcare Conference, 2018
2017
Vicus: Exploiting local structures to improve network-based analysis of biological data.
PLoS Comput. Biol., 2017
Incorporating networks in a probabilistic graphical model to find drivers for complex human diseases.
PLoS Comput. Biol., 2017
2016
Bioinform., 2016
2015
Combining exome and gene expression datasets in one graphical model of disease to empower the discovery of disease mechanisms.
CoRR, 2015
2014
A probabilistic approach to explore human miRNA targetome by integrating miRNA-overexpression data and sequence information.
Bioinform., 2014
2012
Detecting microRNAs of high influence on protein functional interaction networks: a prostate cancer case study.
BMC Syst. Biol., 2012
Proceedings of the Biocomputing 2012: Proceedings of the Pacific Symposium, 2012
2011
Unsupervised detection of genes of influence in lung cancer using biological networks.
Bioinform., 2011
2009
2006
Proceedings of the Statistical Network Analysis: Models, Issues, and New Directions, 2006
2005
Proceedings of the 3rd international workshop on Link discovery, 2005
2004
Proceedings of the Machine Learning, 2004
2001
Artificial neural network approach to data analysis and parameter estimation in experimental spectroscopy.
Informatica (Slovenia), 2001