Term of the Month Precision Medicine James Tabery December 8, 2023 James Tabery | December 8, 2023 Every month, ETAI will be sharing a term or concept of the month […]
Precision Medicine
Dr. Xiaoqian Jiang: Sensitive Data Detection with High-Throughput Machine Learning Models in Electronic Health Records
Dr. Jiang explored how a groundbreaking discovery was utilized to generate 30 metadata-based features through machine learning for the automatic detection of PHI fields in structured Electronic Health Record (EHR) data. […]
Dr. Babak Salimi: Certifying Fair Predictive Models in the Face of Selection Bias
Dr. Salimi offered insights for data management, machine learning, and responsible data science, emphasizing the significance of handling selection bias in algorithmic decision-making. […]
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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. […]
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. […]