AIMC Topic: Aged, 80 and over
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Radiomics-based MRI model to predict hypoperfusion in lacunar infarction.
Magnetic resonance imaging
Mar 21, 2025
BACKGROUND: Approximately 20-30 % of patients with acute ischemic stroke due to lacunar infarction experience early neurological deterioration (END) within the first three days after onset, leading to disability or more severe sequelae. Hemodynamic p...
AI-based deformable hippocampal mesh reflects hippocampal morphological characteristics in relation to cognition in healthy older adults.
NeuroImage
Mar 21, 2025
Magnetic resonance imaging (MRI)-derived hippocampus measurements have been associated with different cognitive domains. The knowledge of hippocampal structural deformations as we age has contributed to our understanding of the overall aging process....
Using Machine Learning to Identify Social Determinants of Health that Impact Discharge Disposition for Hospitalized Patients.
Journal of the American Medical Directors Association
Mar 20, 2025
OBJECTIVE: To identify self-reported social determinants of health (SDOH) among hospitalized patients that predict discharge to a skilled nursing facility (SNF).
Deep learning-based normative database of anterior chamber dimensions for angle closure assessment: the Singapore Chinese Eye Study.
The British journal of ophthalmology
Mar 20, 2025
BACKGROUND/ AIMS: The lack of context for anterior segment optical coherence tomography (ASOCT) measurements impedes its clinical utility. We established the normative distribution of anterior chamber depth (ACD), area (ACA) and width (ACW) and lens ...
Enhanced machine learning predictive modeling for delirium in elderly ICU patients with COPD and respiratory failure: A retrospective study based on MIMIC-IV.
PloS one
Mar 20, 2025
BACKGROUND AND OBJECTIVE: Elderly patients with Chronic obstructive pulmonary disease (COPD) and respiratory failure admitted to the intensive care unit (ICU) have a poor prognosis, and the occurrence of delirium further worsens outcomes and increase...
Machine learning models for enhanced diagnosis and risk assessment of prostate cancer with Ga-PSMA-617 PET/CT.
European journal of radiology
Mar 19, 2025
OBJECTIVE: Prostate cancer (PCa) is highly heterogeneous, making early detection of adverse pathological features crucial for improving patient outcomes. This study aims to predict PCa aggressiveness and identify radiomic and protein biomarkers assoc...
Middle Aged
Risk Assessment
Positron Emission Tomography Computed Tomography
Prostatic Neoplasms
Gallium Isotopes
Prostate-Specific Antigen
Machine Learning
Aged, 80 and over
Heterocyclic Compounds, 1-Ring
Radiopharmaceuticals
Sensitivity and Specificity
Retrospective Studies
Dipeptides
Biomarkers, Tumor
Aged
Gallium Radioisotopes
Male
Humans
Uncovering hidden subtypes in dementia: An unsupervised machine learning approach to dementia diagnosis and personalization of care.
Journal of biomedical informatics
Mar 19, 2025
OBJECTIVE: Dementia represents a growing public health challenge, affecting an increasing number of individuals. It encompasses a broad spectrum of cognitive impairments, ranging from mild to severe stages, each of which demands varying levels of car...
Identification of heart failure subtypes using transformer-based deep learning modelling: a population-based study of 379,108 individuals.
EBioMedicine
Mar 19, 2025
BACKGROUND: Heart failure (HF) is a complex syndrome with varied presentations and progression patterns. Traditional classification systems based on left ventricular ejection fraction (LVEF) have limitations in capturing the heterogeneity of HF. We a...
Predicting postoperative pulmonary infection in elderly patients undergoing major surgery: a study based on logistic regression and machine learning models.
BMC pulmonary medicine
Mar 19, 2025
BACKGROUND: Postoperative pulmonary infection (POI) is strongly associated with a poor prognosis and has a high incidence in elderly patients undergoing major surgery. Machine learning (ML) algorithms are increasingly being used in medicine, but the ...
Machine learning prediction model for functional prognosis of acute ischemic stroke based on MRI radiomics of white matter hyperintensities.
BMC medical imaging
Mar 19, 2025
OBJECTIVE: The purpose of the current study is to explore the value of a nomogram that integrates clinical factors and MRI white matter hyperintensities (WMH) radiomics features in predicting the prognosis at 90 days for patients with acute ischemic ...
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