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Results for "chronic kidney disease"

Community-Based Early-Stage Chronic Kidney Disease Screening using Explainable Machine Learning for Low-Resource Settings

arXiv ·

This paper introduces an explainable machine learning framework for early-stage chronic kidney disease (CKD) screening, specifically designed for low-resource settings in Bangladesh and South Asia. The framework utilizes a community-based dataset from Bangladesh and evaluates multiple ML classifiers with feature selection techniques. Results show that the ML models achieve high accuracy and sensitivity, outperforming existing screening tools and demonstrating strong generalizability across independent datasets from India, the UAE, and Bangladesh.

The AI will see you now

MBZUAI ·

MBZUAI is developing AI algorithms to intelligently process data from wearables and home sensors for remote patient monitoring. The algorithms aim to analyze multiple strands of health data to provide a more comprehensive view of a patient's health, distinguishing between genuine emergencies and benign situations. MBZUAI's provost, Professor Fakhri Karray, believes this approach could handle 20-25% of diagnoses virtually, reducing the burden on healthcare systems. Why it matters: This research could significantly improve healthcare efficiency and accessibility in the UAE and beyond by enabling more effective remote patient monitoring and reducing unnecessary hospital visits.

AI and Biomedicine: the Hospital of the Future

MBZUAI ·

Pierre Baldi from UC Irvine presented applications of AI to biomedicine, covering molecular-level analysis of circadian rhythms, real-time polyp detection in colonoscopy videos, and prediction of post-operative adverse outcomes. He discussed integrating AI in future AI-driven hospitals. The presentation was likely part of a panel discussion hosted by MBZUAI in collaboration with the Manara Center for Coexistence and Dialogue. Why it matters: This highlights the growing interest in AI applications within the healthcare sector in the UAE, particularly through institutions like MBZUAI.

RNA-based approach identified for treatment of premature aging and associated diseases

KAUST ·

KAUST researchers, in collaboration with the Salk Institute and Altos Labs, have identified a class of RNA (LINE-1) that, when compromised, leads to accelerated aging, as seen in progeria. They devised an antisense RNA strategy to block the aberrant function of L1 RNA, reversing the disease in mice and patient-derived cells. Published in Science Translational Medicine, the research suggests that targeting LINE-1 RNA could treat progeroid syndromes and other age-related diseases. Why it matters: This RNA-based approach provides a potential therapeutic avenue for treating premature aging diseases and extending human health span in the region and globally.