Precision PHI Screening
This term reflects the paper’s emphasis on using high-throughput machine learning models to precisely detect sensitive data, specifically Protected Health Information (PHI), in electronic health records. […]
Author: daniweng
Posts by daniweng
Data Quality and Algorithmic Fairness
In today’s digital age, algorithmic decision-making systems play a crucial role in fields like credit scoring and medical diagnoses. While they are often praised for being ‘objective,’ these systems can exhibit biases, mostly stemming from the data they rely on. […]
Dr. Bradley Malin: One Size Does Not Fit All: How to Build Respectful Cohorts for Biomedical Data Science
Dr. Malin drew upon examples from large-scale data-driven projects like the EMR and bio-repository at Vanderbilt University Medical Center, the eMERGE consortium of the NIH, and the All of Us Research Program, aiming to create a comprehensive database of EMRs, genome sequences, and mHealth records from one million Americans. […]
Dignitary Privacy
“Dignitary privacy is based on a belief that privacy is intrinsically valuable, whereas resource privacy is based on a belief that privacy is simply a tool that has instrumental value.”
Hughes, RL David. […]
Dr. Debra Mathews: Using Population Descriptors in Genetics and Genomics Research: A New Framework for an Evolving Field — Lessons from a NASEM Consensus Study for AI-READI
Dr Mathews provided an overview of the recent NASEM consensus study report that focused on the use of race and ethnicity and other population descriptors in genomics research, including the recommendations made by the committee. […]
Social License
In a recent article in the Stanford Social Innovation Review, a group of authors “define a social license as the process of building trust and legitimacy from ongoing (i.e., constantly renewed) community or stakeholder engagement and acceptance of how data is being accessed and reused.” […]
Joseph Yracheta: The Dissonance between Scientific Altruism & Capitalist Extraction for & from the Amerindigenous
American Indians experience elevated rates of health conditions like diabetes, chronic kidney disease, and cardiovascular disease, as well as greater exposure to environmental hazards. […]
Data Subject
The term data subject refers to an individual whose data are used in data science research using de-identified, public datasets. […]
Dr. Aaron Goldenberg: Unanswered ELSI Questions in the Development of Biomedical Repositories: Privacy, Equity, and Stewardship
Dr. Goldenberg discussed the evolving ethical, legal, and social concerns (ELSI) associated with biorepositories and biobanking. […]
Dr. Berk Ustun: Towards Personalization without Harm
Dr. Ustun discussed how machine learning models, personalized with sensitive features like sex, age group, and HIV status, can perform better for populations but worse for specific groups, potentially causing harm. […]
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