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Development and evaluation of machine learning training strategies for neonatal mortality prediction using multicountry data.
Scientific reports
Jul 7, 2025
Neonatal mortality poses a critical challenge in global health, particularly in low- and middle-income countries. Leveraging advancements in technology, such as machine learning (ML) algorithms, offers the potential to improve neonatal care by enabli...
Nuclear morphometrics coupled with machine learning identifies dynamic states of senescence across age.
Nature communications
Jul 7, 2025
Cellular senescence is an irreversible state of cell cycle arrest with a complex role in tissue repair, aging, and disease. However, inconsistencies in identifying cellular senescence have led to varying conclusions about their functional significanc...
Cost-effectiveness analysis of robotic exoskeleton versus conventional physiotherapy for stroke rehabilitation in Singapore from a health system perspective.
BMJ open
Jul 7, 2025
OBJECTIVES: This study conducted a comprehensive probabilistic cost-effectiveness analysis comparing robotic exoskeleton therapy to conventional physiotherapy for stroke rehabilitation in Singapore, focusing on three patient groups categorised by the...
Identifying and characterising asthma subgroups at high risk of severe exacerbations using machine learning and longitudinal real-world data.
BMJ health & care informatics
Jul 7, 2025
OBJECTIVES: To identify and characterise distinct subgroups of patients with asthma with severe acute exacerbations (AEs) by using a multistep clustering methodology that combines supervised and unsupervised machine learning.
Scalable Precision Psychiatry With an Objective Measure of Psychological Stress: Prospective Real-World Study.
Journal of medical Internet research
Jul 7, 2025
BACKGROUND: Before meaningful progress toward precision psychiatry is possible, objective (unbiased) assessment of patient mental well-being must be validated and adopted broadly.
External validation of a prediction model for disability and pain after lumbar disc herniation surgery: a prospective international registry-based cohort study.
Acta orthopaedica
Jul 7, 2025
BACKGROUND AND PURPOSE: We aimed to externally validate machine learning models developed in Norway by evaluating their predictive outcome of disability and pain 12 months after lumbar disc herniation surgery in a Swedish and Danish cohort.
Machine learning-based prediction of short- and long-term mortality for shared decision-making in older hip fracture patients: the Dutch Hip Fracture Audit algorithms in 74,396 cases.
Acta orthopaedica
Jul 7, 2025
BACKGROUND AND PURPOSE: Treatment-related shared decision-making (SDM) in older adults with hip fractures is complex due to the need to balance patient-specific factors such as life goals, frailty, and surgical risks. It includes considerations such...
Understanding the determinants of treated bed net use in Ethiopia: A machine learning classification approach using PMA Ethiopia 2023 survey data.
PloS one
Jul 7, 2025
INTRODUCTION: Malaria remains a significant public health challenge in Ethiopia, with over 7.3 million cases and 1,157 deaths reported between January 1 and October 20, 2024. Despite extensive distribution campaigns, 35% of insecticide-treated nets (...
Identification and validation of parthanatos-related genes in end-stage renal disease.
Renal failure
Jul 6, 2025
BACKGROUND: End-Stage Renal Disease (ESRD) is a severe chronic kidney disease with a rising global incidence, often accompanied by various complications, severely impacting patients' quality of life. Parthanatos plays a crucial role in the pathogenes...
Artificial intelligence-assisted longitudinal assessment of coronary artery calcification in the Korean lung cancer screening CT program.
Clinical imaging
Jul 6, 2025
PURPOSE: The clinical implications of coronary artery calcification (CAC) growth remain underexplored. This study aims to assess CAC growth and its association with adverse cardiovascular events (ACEs) in individuals undergoing lung cancer screening ...
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