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Open AccessDevelopment and application of a weighted change score to evaluate interventions for vasomotor symptoms in patients with breast cancer using regression trees: a cohort study
Vasomotor symptoms (VMS) are common among individuals with breast cancer (BC) and poorly managed symptoms are associated with reduced quality of life, treatment discontinuation, and poorer breast cancer outcom...
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Open AccessAn evaluation of the replicability of analyses using synthetic health data
Synthetic data generation is being increasingly used as a privacy preserving approach for sharing health data. In addition to protecting privacy, it is important to ensure that generated data has high utility....
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Open AccessA comparison of synthetic data generation and federated analysis for enabling international evaluations of cardiovascular health
Sharing health data for research purposes across international jurisdictions has been a challenge due to privacy concerns. Two privacy enhancing technologies that can enable such sharing are synthetic data gen...
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Open AccessA method for generating synthetic longitudinal health data
Getting access to administrative health data for research purposes is a difficult and time-consuming process due to increasingly demanding privacy regulations. An alternative method for sharing administrative ...
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Open AccessUsing machine learning to predict individual patient toxicities from cancer treatments
Machine learning (ML) is a powerful tool for interrogating datasets and learning relationships between multiple variables. We utilized a ML model to identify those early breast cancer (EBC) patients at highes...
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Vasomotor symptoms in early breast cancer—a “real world” exploration of the patient experience
Despite the frequency of vasomotor symptoms (VMS) in patients with early breast cancer (EBC), their optimal management remains unknown. A patient survey was performed to determine perspectives on this importan...
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Article
Open AccessReconciling public health common good and individual privacy: new methods and issues in geoprivacy
This article provides a state-of-the-art summary of location privacy issues and geoprivacy-preserving methods in public health interventions and health research involving disaggregate geographic data about ind...
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Open AccessAdvancing data science in drug development through an innovative computational framework for data sharing and statistical analysis
Novartis and the University of Oxford’s Big Data Institute (BDI) have established a research alliance with the aim to improve health care and drug development by making it more efficient and targeted. Using a ...
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Open AccessEvaluating the re-identification risk of a clinical study report anonymized under EMA Policy 0070 and Health Canada Regulations
Regulatory agencies, such as the European Medicines Agency and Health Canada, are requiring the public sharing of clinical trial reports that are used to make drug approval decisions. Both agencies have provid...
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Open AccessA linear programming model for preserving privacy when disclosing patient spatial information for secondary purposes
A linear programming (LP) model was proposed to create de-identified data sets that maximally include spatial detail (e.g., geocodes such as ZIP or postal codes, census blocks, and locations on maps) while com...
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Article
Open AccessPolicy recommendations for addressing privacy challenges associated with cell-based research and interventions
The increased use of human biological material for cell-based research and clinical interventions poses risks to the privacy of patients and donors, including the possibility of re-identification of individual...
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Open AccessEvaluating the risk of patient re-identification from adverse drug event reports
Our objective was to develop a model for measuring re-identification risk that more closely mimics the behaviour of an adversary by accounting for repeated attempts at matching and verification of matches, and...
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Open AccessEstimating the re-identification risk of clinical data sets
De-identification is a common way to protect patient privacy when disclosing clinical data for secondary purposes, such as research. One type of attack that de-identification protects against is linking the di...
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Article
Open AccessDe-identifying a public use microdata file from the Canadian national discharge abstract database
The Canadian Institute for Health Information (CIHI) collects hospital discharge abstract data (DAD) from Canadian provinces and territories. There are many demands for the disclosure of this data for research...
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Open AccessThe re-identification risk of Canadians from longitudinal demographics
The public is less willing to allow their personal health information to be disclosed for research purposes if they do not trust researchers and how researchers manage their data. However, the public is more c...
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Open AccessPhysician privacy concerns when disclosing patient data for public health purposes during a pandemic influenza outbreak
Privacy concerns by providers have been a barrier to disclosing patient information for public health purposes. This is the case even for mandated notifiable disease reporting. In the context of a pandemic it ...
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Methods for the de-identification of electronic health records for genomic research
Electronic health records are increasingly being linked to DNA repositories and used as a source of clinical information for genomic research. Privacy legislation in many jurisdictions, and most research ethic...
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Open AccessA method for managing re-identification risk from small geographic areas in Canada
A common disclosure control practice for health datasets is to identify small geographic areas and either suppress records from these small areas or aggregate them into larger ones. A recent study provided a m...
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Article
A survey: technology in a pediatric day care setting