AIMC Topic: Aged
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Machine Learning-Based Model for Prediction of Post-Stroke Cognitive Impairment in Acute Ischemic Stroke: A Cross-Sectional Study.
Neurology India
Dec 17, 2024
BACKGROUND AND OBJECTIVE: Early identification of post-stroke cognitive impairment (PSCI) is an important challenge for clinicians. In this study, we aimed to build a machine learning-based prediction model for PSCI and uncover potential risk factors...
Predicting grip strength-related frailty in middle-aged and older Chinese adults using interpretable machine learning models: a prospective cohort study.
Frontiers in public health
Dec 17, 2024
INTRODUCTION: Frailty is an emerging global health burden, and there is no consensus on the precise prediction of frailty. We aimed to explore the association between grip strength and frailty and interpret the optimal machine learning (ML) model usi...
Clinical characteristics of adrenal crisis in 371 adult patients with glucocorticoid-induced adrenal insufficiency.
Frontiers in endocrinology
Dec 17, 2024
BACKGROUND: Glucocorticoid-induced adrenal insufficiency (GIAI) is a hypothalamic-pituitary-adrenal (HPA) axis dysfunction caused by long-term use of exogenous steroids. Adrenal crisis (AC) is an acute complication of GIAI and one of the reasons for ...
Evaluating Human-Robot Interactions to Support Healthy Aging-in-Place.
Journal of applied gerontology : the official journal of the Southern Gerontological Society
Dec 16, 2024
Declines in older adults' cognitive and physical health pose challenges to maintaining their independence. Robots can improve independent living and facilitate aging-in-place. Despite recent innovations in healthcare robotics, the use of robots has n...
Interpretable Deep-learning Model Based on Superb Microvascular Imaging for Noninvasive Diagnosis of Interstitial Fibrosis in Chronic Kidney Disease.
Academic radiology
Dec 16, 2024
RATIONALE AND OBJECTIVES: To develop an interpretable deep learning (XDL) model based on superb microvascular imaging (SMI) for the noninvasive diagnosis of the degree of interstitial fibrosis (IF) in chronic kidney disease (CKD).
SMART: Development and Application of a Multimodal Multi-organ Trauma Screening Model for Abdominal Injuries in Emergency Settings.
Academic radiology
Dec 16, 2024
RATIONALE AND OBJECTIVES: Effective trauma care in emergency departments necessitates rapid diagnosis by interdisciplinary teams using various medical data. This study constructed a multimodal diagnostic model for abdominal trauma using deep learning...
Machine Learning for In-hospital Mortality Prediction in Critically Ill Patients With Acute Heart Failure: A Retrospective Analysis Based on the MIMIC-IV Database.
Journal of cardiothoracic and vascular anesthesia
Dec 16, 2024
BACKGROUND: The incidence, mortality, and readmission rates for acute heart failure (AHF) are high, and the in-hospital mortality for AHF patients in the intensive care unit (ICU) is higher. However, there is currently no method to accurately predict...
Noncontrast MRI-based machine learning and radiomics signature can predict the severity of primary lower limb lymphedema.
Journal of vascular surgery. Venous and lymphatic disorders
Dec 16, 2024
OBJECTIVE: According to International Lymphology Society guidelines, the severity of lymphedema is determined by the difference in volume between the affected limb and the healthy side divided by the volume of the healthy side. However, this method o...
Exploring phenotypes to improve long-term mortality risk stratification in obstructive sleep apnea through a machine learning approach: an observational cohort study.
European journal of internal medicine
Dec 16, 2024
BACKGROUND: Obstructive sleep apnea (OSA) is a heterogeneous sleep disorder for which the identification of phenotypes might help for risk stratification for long-term mortality. Thus, the aim of the study was to identify distinct phenotypes of OSA a...
Concordance-based Predictive Uncertainty (CPU)-Index: Proof-of-concept with application towards improved specificity of lung cancers on low dose screening CT.
Artificial intelligence in medicine
Dec 16, 2024
In this paper, we introduce a novel concordance-based predictive uncertainty (CPU)-Index, which integrates insights from subgroup analysis and personalized AI time-to-event models. Through its application in refining lung cancer screening (LCS) predi...
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