AIMC Topic: Aged

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Personalized Exercise Programs Based upon Remote Assessment of Motor Fitness: A Pilot Study among Healthy People Aged 65 Years and Older.

Gerontology
BACKGROUND: The World Health Organization has recently updated exercise guidelines for people aged >65 years, emphasizing the inclusion of multiple fitness components. However, without adequate recognition of individual differences, these guidelines ...

Implementing an Individual-Centric Discharge Process across Singapore Public Hospitals.

International journal of environmental research and public health
Singapore is one of the first known countries to implement an individual-centric discharge process across all public hospitals to manage frequent admissions-a perennial challenge for public healthcare, especially in an aging population. Specifically,...

Machine learning identifies ICU outcome predictors in a multicenter COVID-19 cohort.

Critical care (London, England)
BACKGROUND: Intensive Care Resources are heavily utilized during the COVID-19 pandemic. However, risk stratification and prediction of SARS-CoV-2 patient clinical outcomes upon ICU admission remain inadequate. This study aimed to develop a machine le...

Random walks on B distributed resting-state functional connectivity to identify Alzheimer's disease and Mild Cognitive Impairment.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: Resting-state functional connectivity reveals a promising way for the early detection of dementia. This study proposes a novel method to accurately classify Healthy Controls, Early Mild Cognitive Impairment, Late Mild Cognitive Impairment,...

Comparative analysis of machine learning approaches to classify tumor mutation burden in lung adenocarcinoma using histopathology images.

Scientific reports
Both histologic subtypes and tumor mutation burden (TMB) represent important biomarkers in lung cancer, with implications for patient prognosis and treatment decisions. Typically, TMB is evaluated by comprehensive genomic profiling but this requires ...

Predicting Incident Heart Failure in Women With Machine Learning: The Women's Health Initiative Cohort.

The Canadian journal of cardiology
BACKGROUND: Heart failure (HF) is a leading cause of cardiac morbidity among women, whose risk factors differ from those in men. We used machine-learning approaches to develop risk- prediction models for incident HF in a cohort of postmenopausal wome...

Accounting for symptom heterogeneity can improve neuroimaging models of antidepressant response after electroconvulsive therapy.

Human brain mapping
Depression symptom heterogeneity limits the identifiability of treatment-response biomarkers. Whether improvement along dimensions of depressive symptoms relates to separable neural networks remains poorly understood. We build on work describing thre...