AIMC Topic: Middle Aged
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Machine Learning Model for Risk Prediction of Prolonged Intensive Care Unit in Patients Receiving Intra-aortic Balloon Pump Therapy during Coronary Artery Bypass Graft Surgery.
Journal of cardiovascular translational research
Dec 24, 2024
This study aimed to construct machine learning models and predict prolonged intensive care units (ICU) stay in patients receiving perioperative intra-aortic balloon pump (IABP) therapy during cardiac surgery. 236 patients were divided into the normal...
Retrospective Studies
Intensive Care Units
Female
Reproducibility of Results
Risk Factors
Humans
Machine Learning
Decision Support Techniques
Time Factors
Treatment Outcome
Predictive Value of Tests
Coronary Artery Bypass
Intra-Aortic Balloon Pumping
Aged
Male
Middle Aged
Risk Assessment
Length of Stay
Ensemble learning-based radiomics model for discriminating brain metastasis from glioblastoma.
European journal of radiology
Dec 24, 2024
OBJECTIVE: Differentiating between brain metastasis (BM) and glioblastoma (GBM) preoperatively is challenging due to their similar imaging features on conventional brain MRI. This study aimed to enhance diagnostic accuracy through a machine learning ...
Computer model for gait assessments in Parkinson's patients using a fuzzy inference model and inertial sensors.
Artificial intelligence in medicine
Dec 24, 2024
Patients with Parkinson's disease (PD) in the moderate and severe stages can present several walk alterations. They can show slow movements and difficulty initiating, varying, or interrupting their gait; freezing; short steps; speed changes; shufflin...
Screening prediction models using artificial intelligence for moderate-to-severe obstructive sleep apnea in patients with acute ischemic stroke.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Dec 24, 2024
BACKGROUND: Obstructive sleep apnea (OSA) is common after stroke. Still, routine screening of OSA with polysomnography (PSG) is often unfeasible in clinical practice, primarily because of how limited resources are and the physical condition of patien...
SymScore: Machine learning accuracy meets transparency in a symbolic regression-based clinical score generator.
Computers in biology and medicine
Dec 24, 2024
Self-report questionnaires play a crucial role in healthcare for assessing disease risks, yet their extensive length can be burdensome for respondents, potentially compromising data quality. To address this, machine learning-based shortened questionn...
Predicting the risk of cardiovascular disease in adults exposed to heavy metals: Interpretable machine learning.
Ecotoxicology and environmental safety
Dec 24, 2024
Machine learning exhibits excellent performance in terms of predictive power. We aimed to construct an interpretable machine learning model utilizing National Health and Nutrition Examination Survey data to investigate the relationship between heavy ...
Non-invasive screening for laryngeal cancer using the oral cavity as a proxy for differentiation of laryngeal cancer versus leukoplakia: A novel application of ESS technology and artificial intelligence supported statistical modeling.
American journal of otolaryngology
Dec 24, 2024
OBJECTIVE: This preliminary study tested whether non-invasive, remote Elastic Scattering Spectroscopy (ESS) measurements obtained in the oral cavity can be used as a proxy to accurately differentiate between patients with laryngeal cancer versus lary...
Predicting macular hole surgery outcomes: Integrating preoperative OCT features with supervised machine learning statistical models.
Indian journal of ophthalmology
Dec 24, 2024
PURPOSE: To evaluate various supervised machine learning (ML) statistical models to predict anatomical outcomes after macular hole (MH) surgery using preoperative optical coherence tomography (OCT) features.
3-Dimensional morphological characterization of neuroretinal microglia in Alzheimer's disease via machine learning.
Acta neuropathologica communications
Dec 24, 2024
Alzheimer's Disease (AD) is a debilitating neurodegenerative disease that affects 47.5 million people worldwide. AD is characterised by the formation of plaques containing extracellular amyloid-β (Aβ) and neurofibrillary tangles composed of hyper-pho...
Prognostic value of a composite physiologic index developed by adding bronchial and hyperlucent volumes quantified via artificial intelligence technology.
Respiratory research
Dec 24, 2024
BACKGROUND: The composite physiologic index (CPI) was developed to estimate the extent of interstitial lung disease (ILD) in idiopathic pulmonary fibrosis (IPF) patients based on pulmonary function tests (PFTs). The CALIPER-revised version of the CPI...
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