Publications by authors named "T M Bright"
Article Synopsis
- Machine learning is used to improve the screening of perinatal mood and anxiety disorders (PMADs), highlighting the need to address biases in electronic health records (EHRs) that can affect predictive models.
- The study took place from 2020 to 2023 at Cedars-Sinai Medical Center and included birthing patients aged 14 to 59 who had recent births.
- Multiple machine learning models were assessed for their ability to predict PMAD risks, focusing on fairness and accuracy, specifically comparing outcomes across different racial and ethnic groups.
Background: Some patients with gastroesophageal reflux (GERD) experience extraesophageal symptoms, which are considered due to laryngopharyngeal reflux (LPR). Most studies evaluating fundoplication for LPR report outcomes from individuals who also have typical esophageal GERD symptoms. Information is limited for patients with LPR but no GERD symptoms.
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- The American Medical Informatics Association (AMIA) established a Task Force on Diversity, Equity, and Inclusion (DEI) to combat systemic racism and health disparities highlighted by events like police brutality and COVID-19's impact on Black communities.
- The Task Force, with 20 core members and additional volunteers, developed a series of DEI recommendations over nine months, including creating a logic model and conducting a review of DEI initiatives from other organizations.
- The Task Force's efforts aim to support marginalized groups, expand the research focus on equity issues, and position AMIA as a leader in DEI, emphasizing the need for continuous transformation within the field of informatics.*
Article Synopsis
- The authors talk about how important it is to include everyone, especially LGBTQ+ people, in science and technology education and AI research.
- They point out the problems that queer scientists face and how better educational resources can help them.
- The authors want to create a supportive environment where everyone can work together respectfully, no matter their background.
This study aimed to compare the agreement between three-dimensional motion capture and vertical ground reaction force (vGRF) in identifying the point of dumbbell (DB) release during a countermovement jump with accentuated eccentric loading (CMJ), and to examine the influence of the vGRF analysis method on the reliability and magnitude of CMJ variables. Twenty participants (10 male, 10 female) completed five maximal effort CMJ at 20% and 30% of body mass (CMJ and CMJ, respectively) using DBs. There was large variability between methods in both loading conditions, as indicated by the wide limits of agreement (CMJ = -0.
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