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Unveiling diabetes onset: Optimized XGBoost with Bayesian optimization for enhanced prediction.
PLoS One
January 2025
Department of Computer Science and Information Systems, College of Applied Sciences, AlMaarefa University, Ad Diriyah, Riyadh, Kingdom of Saudi Arabia.
Diabetes, a chronic condition affecting millions worldwide, necessitates early intervention to prevent severe complications. While accurately predicting diabetes onset or progression remains challenging due to complex and imbalanced datasets, recent advancements in machine learning offer potential solutions. Traditional prediction models, often limited by default parameters, have been superseded by more sophisticated approaches.
View Article and Find Full Text PDFRejunctive Moves Toward Systemic Healing: A Contextual Family Therapy Approach to Father's Absence.
Fam Process
March 2025
Couple and Family Therapy Program, Alliant International University, Irvine, California, USA.
The phenomena of father's absence and the disruption of a family unit due to social justice issues like incarceration and mental health/substance misuse challenges are widely documented, and their effects on the whole family are well established in the literature. This paper specifically examines how systemic inequities like racism contribute to destructive entitlements that can occur transgenerationally within families affected by father's absence. The consideration of racial trauma is crucial, as father's absence and family disruption are not limited to any one racial or ethnic group, but the effects are often exacerbated for families of color due to the intersecting impacts of systemic racism.
View Article and Find Full Text PDFPrenatal diagnosis following preimplantation genetic testing for monogenic conditions: a single centre record linkage study.
J Assist Reprod Genet
January 2025
University of Melbourne, Parkville, Australia, VIC.
Purpose: Professional bodies currently advise all pregnant individuals undertake confirmatory prenatal diagnostic testing following preimplantation genetic testing for monogenic conditions (PGT-M). We aimed to ascertain the uptake of prenatal diagnostic testing following PGT-M in a large single-centre population.
Methods: This observational linkage study was undertaken using routinely collected outcome data from PGT-M cycles performed at one of Australia's largest PGT-M providers and a statewide dataset of all prenatal samples undergoing cytogenetic analysis in Victoria, Australia, between 2015 and 2022.
Moral Complexity in Traffic: Advancing the ADC Model for Automated Driving Systems.
Sci Eng Ethics
January 2025
Department of Philosophy and Religious Studies, North Carolina State University, Raleigh, NC, USA.
The incorporation of ethical settings in Automated Driving Systems (ADSs) has been extensively discussed in recent years with the goal of enhancing potential stakeholders' trust in the new technology. However, a comprehensive ethical framework for ADS decision-making, capable of merging multiple ethical considerations and investigating their consistency is currently missing. This paper addresses this gap by providing a taxonomy of ADS decision-making based on the Agent-Deed-Consequences (ADC) model of moral judgment.
View Article and Find Full Text PDFEvaluating human ability to distinguish between ChatGPT-generated and original scientific abstracts.
Updates Surg
January 2025
Department of Surgery, St. Paul's Hospital, 1081 Burrard St., Vancouver, BC, V6Z 1Y6, Canada.
This study aims to analyze the accuracy of human reviewers in identifying scientific abstracts generated by ChatGPT compared to the original abstracts. Participants completed an online survey presenting two research abstracts: one generated by ChatGPT and one original abstract. They had to identify which abstract was generated by AI and provide feedback on their preference and perceptions of AI technology in academic writing.
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