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Robust and interpretable AI-guided marker for early dementia prediction in real-world clinical settings.
EClinicalMedicine
August 2024
Department of Psychology, University of Cambridge, Cambridge, CB2 3EB, United Kingdom.
Background: Predicting dementia early has major implications for clinical management and patient outcomes. Yet, we still lack sensitive tools for stratifying patients early, resulting in patients being undiagnosed or wrongly diagnosed. Despite rapid expansion in machine learning models for dementia prediction, limited model interpretability and generalizability impede translation to the clinic.
View Article and Find Full Text PDFBackground: People with Alzheimer's disease (AD) exhibit varying clinical trajectories. There is a need to predict future AD-related outcomes such as morbidity and mortality using clinical profile at the point of care.
Objective: To stratify AD patients based on baseline clinical profiles (up to two years prior to AD diagnosis) and update the model after AD diagnosis to prognosticate future AD-related outcomes.
Unlocking the Vitamin Puzzle: Investigating Levels in People With Alzheimer's Disease Versus Healthy Controls Through Systematic Review and Network Meta-Analysis.
J Hum Nutr Diet
February 2025
Department of Biostatistics and Medical Informatics, University College of Medical Sciences, Delhi, India.
The progression of Alzheimer's disease (AD) is intricately tied to the impairment of neurons, crucial for neurological functions. Despite extensive research, the precise mechanism underlying AD development remains elusive due to its multifaceted aetiology. Vitamin deficiency has emerged as a notable contributor to AD onset and progression, exerting a significant influence on brain function.
View Article and Find Full Text PDFBenchmarking Alzheimer's disease prediction: personalised risk assessment using polygenic risk scores across various methodologies and genome-wide studies.
Alzheimers Res Ther
January 2025
UK Dementia Research Institute at Cardiff, Cardiff University, Hadyn Ellis Building, Maindy Road, Cardiff, CF24 4HQ, UK.
Background: The success of selecting high risk or early-stage Alzheimer's disease individuals for the delivery of clinical trials depends on the design and the appropriate recruitment of participants. Polygenic risk scores (PRS) show potential for identifying individuals at risk for Alzheimer's disease (AD). Our study comprehensively examines AD PRS utility using various methods and models.
View Article and Find Full Text PDFAging with HIV: The Burden of Comorbidities, Polypharmacy, and Drug Interactions in Korean People Living with HIV Aged ≥50 Years.
Infect Chemother
December 2024
Department of Infectious Diseases, Chonnam National University Hospital, Gwangju, Korea.
Background: The life expectancy of people living with human immunodeficiency virus (PLWH) has significantly improved with advancements in antiretroviral therapy (ART). However, aging PLWH face a growing burden of non-communicable diseases (NCDs), polypharmacy, and drug-drug interactions (DDIs), which pose challenges in their management. This study investigates the prevalence of NCDs, polypharmacy, and DDIs among PLWH aged ≥50 years in Korea and their impact on quality of life (QOL).
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