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Machine learning identifies KRT8 dysregulation and endothelial remodeling in Moyamoya disease.

Scientific reports
Moyamoya disease (MMD) is a rare occlusive cerebrovascular disease, and its pathological mechanism remains unclear at present. The abnormal vascular remodeling may be involved in vascular endothelial cells. In this study, RNA seq was performed on the...

Deep learning-based video analysis for automatically detecting penetration and aspiration in videofluoroscopic swallowing study.

Scientific reports
The videofluoroscopic swallowing study (VFSS) is the gold standard for diagnosing dysphagia, but its interpretation is time-consuming and requires expertise. This study developed a deep learning model for automatically detecting penetration and aspir...

Enhanced particle swarm optimization for feature selection in SVM-based Alzheimer's disease diagnosis.

Scientific reports
Alzheimer's Disease (AD) is a progressive neurodegenerative disorder marked by neuronal loss, leading to cognitive and behavioral decline. With the aging global population, AD incidence and its socioeconomic burden are increasing. Developing effectiv...

Development and evaluation of machine learning training strategies for neonatal mortality prediction using multicountry data.

Scientific reports
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
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
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
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
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
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
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...