Trustworthiness, a commonly recognized antecedent to trust, can be described as the perception of probabilities, or expectation, that a trusting relationship will result in gains and/or losses from engaging in an encounter that requires trust. […]
Category: Term of the Month
Hallucination
Trustworthiness, a commonly recognized antecedent to trust, can be described as the perception of probabilities, or expectation, that a trusting relationship will result in gains and/or losses from engaging in an encounter that requires trust. […]
Tiffany Problem
Trustworthiness, a commonly recognized antecedent to trust, can be described as the perception of probabilities, or expectation, that a trusting relationship will result in gains and/or losses from engaging in an encounter that requires trust. […]
Trustworthiness
Trustworthiness, a commonly recognized antecedent to trust, can be described as the perception of probabilities, or expectation, that a trusting relationship will result in gains and/or losses from engaging in an encounter that requires trust. […]
Invisible Populations
A subset of the population that is not considered in healthcare clinical trials and are not considered in the data sets for new AI applications. […]
Glamour AI
AI that has little or no meaningful clinical value […]
Causal Fairness in Healthcare
Causal fairness in healthcare refers to an ethical and methodological approach aimed at addressing disparities and ensuring equity in healthcare outcomes by focusing on the underlying causal relationships between interventions and health outcomes. […]
Indigenous Data Sovereignty and Blockchain
Indigenous data sovereignty (IDS) is defined as the right of an Indigenous nation to govern the collection, ownership, and application of data generated by its members. […]
Precision Medicine
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 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. […]