AIMC Topic: Aged

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Risk for ocular hypertension progression to early glaucoma: A predictive model and key predictors.

Photodiagnosis and photodynamic therapy
BACKGROUND: Ocular hypertension (OHT) is the most significant risk factor for glaucoma. We aimed to develop a model for predicting OHT progression to early glaucoma and to identify key predictors.

Predictive models of severe disease in patients with COVID-19 pneumonia at an early stage on CT images using topological properties.

Radiological physics and technology
Prediction of severe disease (SVD) in patients with coronavirus disease (COVID-19) pneumonia at an early stage could allow for more appropriate triage and improve patient prognosis. Moreover, the visualization of the topological properties of COVID-1...

Machine Learning-Based Radiomics in Malignancy Prediction of Pancreatic Cystic Lesions: Evidence from Cyst Fluid Multi-Omics.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
The malignant potential of pancreatic cystic lesions (PCLs) varies dramatically, leading to difficulties when making clinical decisions. This study aimed to develop noninvasive clinical-radiomic models using preoperative CT images to predict the mali...

Gadoxetic acid-enhanced MRI for identifying cholangiocyte phenotype hepatocellular carcinoma by interpretable machine learning: individual application of SHAP.

BMC cancer
PURPOSE: Cholangiocyte phenotype hepatocellular carcinoma (HCC) is highly invasive. This study aims to develop and validate an optimal machine learning model to predict cholangiocyte phenotype HCC based on T1 mapping gadoxetic acid-enhanced MRI and t...

Intermittent hypoxemia during hemodialysis: AI-based identification of arterial oxygen saturation saw-tooth pattern.

BMC nephrology
BACKGROUND: Maintenance hemodialysis patients experience high morbidity and mortality, primarily from cardiovascular and infectious diseases. It was discovered recently that low arterial oxygen saturation (SaO) is associated with a pro-inflammatory p...

F-FDG PET/CT-based deep learning models and a clinical-metabolic nomogram for predicting high-grade patterns in lung adenocarcinoma.

BMC medical imaging
BACKGROUND: To develop and validate deep learning (DL) and traditional clinical-metabolic (CM) models based on 18 F-FDG PET/CT images for noninvasively predicting high-grade patterns (HGPs) of invasive lung adenocarcinoma (LUAD).

Artificial intelligence alert system based on intraluminal view for colonoscopy intubation.

Scientific reports
Mucosal contact of the tip of colonoscopy causes red-out views, and more pressure may result in perforation. There is still a lack of quantitative analysis methods for red-out views. We aimed to develop an artificial intelligence (AI)-based system to...

AI in Home Care-Evaluation of Large Language Models for Future Training of Informal Caregivers: Observational Comparative Case Study.

Journal of medical Internet research
BACKGROUND: The aging population presents an accomplishment for society but also poses significant challenges for governments, health care systems, and caregivers. Elevated rates of functional limitations among older adults, primarily caused by chron...

Explainable Machine Learning Model for Predicting Persistent Sepsis-Associated Acute Kidney Injury: Development and Validation Study.

Journal of medical Internet research
BACKGROUND: Persistent sepsis-associated acute kidney injury (SA-AKI) shows poor clinical outcomes and remains a therapeutic challenge for clinicians. Early identification and prediction of persistent SA-AKI are crucial.

Intraocular lens calculation formula developed using artificial intelligence for ultrasonic biometry.

Arquivos brasileiros de oftalmologia
PURPOSE: We developed an artificial intelligence program for calculating intraocular lenses and analyzed its accuracy rate via ultrasonic biometry. This endeavor is aimed at enhancing precision and efficacy in the selection of intraocular lenses, par...