AIMC Topic: Aged
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Dual Energy CT for Deep Learning-Based Segmentation and Volumetric Estimation of Early Ischemic Infarcts.
Journal of imaging informatics in medicine
Oct 9, 2024
Ischemic changes are not visible on non-contrast head CT until several hours after infarction, though deep convolutional neural networks have shown promise in the detection of subtle imaging findings. This study aims to assess if dual-energy CT (DECT...
Implementation of an AI Algorithm in Clinical Practice to Reduce Missed Incidental Pulmonary Embolisms on Chest CT and Its Impact on Short-Term Survival.
Investigative radiology
Oct 9, 2024
OBJECTIVES: A substantial number of incidental pulmonary embolisms (iPEs) in computed tomography scans are missed by radiologists in their daily routine. This study analyzes the radiological reports of iPE cases before and after implementation of an ...
Predicting Response to Intravesical Bacillus Calmette-Guérin in High-Risk Nonmuscle-Invasive Bladder Cancer Using an Artificial Intelligence-Powered Pathology Assay: Development and Validation in an International 12-Center Cohort.
The Journal of urology
Oct 9, 2024
PURPOSE: There are few markers to identify those likely to recur or progress after treatment with intravesical bacillus Calmette-Guérin (BCG). We developed and validated artificial intelligence (AI)-based histologic assays that extract interpretable ...
Analysis of nailfold capillaroscopy images with artificial intelligence: Data from literature and performance of machine learning and deep learning from images acquired in the SCLEROCAP study.
Microvascular research
Oct 9, 2024
OBJECTIVE: To evaluate the performance of machine learning and then deep learning to detect a systemic scleroderma (SSc) landscape from the same set of nailfold capillaroscopy (NC) images from the French prospective multicenter observational study SC...
Rapid diagnosis and recurrence prediction of choledocholithiasis disease using raw bile with machine learning assisted SERS.
Talanta
Oct 9, 2024
Surface-enhanced Raman spectroscopy (SERS) analysis based on body fluids has been widely applied in disease diagnose. Choledocholithiasis is a widespread and often recurrent digestive system disease, with limited data on factors predicting its format...
Patients' attitudes toward artificial intelligence in dentistry and their trust in dentists.
Oral radiology
Oct 9, 2024
OBJECTIVES: This study intended to evaluate patients' attitudes toward the use of AI in dental radiographic detection of occlusal caries and the impact of AI-based diagnosis on their trust in dentists.
Serum Potassium Monitoring Using AI-Enabled Smartwatch Electrocardiograms.
JACC. Clinical electrophysiology
Oct 9, 2024
BACKGROUND: Hyperkalemia, characterized by elevated serum potassium levels, heightens the risk of sudden cardiac death, particularly increasing risk for individuals with chronic kidney disease and end-stage renal disease (ESRD). Traditional laborator...
A Deep Learning System to Predict Epithelial Dysplasia in Oral Leukoplakia.
Journal of dental research
Oct 9, 2024
Oral leukoplakia (OL) has an inherent disposition to develop oral cancer. OL with epithelial dysplasia (OED) is significantly likely to undergo malignant transformation; however, routine OED assessment is invasive and challenging. This study investig...
Development of HepatIA: A computed tomography annotation platform and database for artificial intelligence training in hepatocellular carcinoma detection at a Brazilian tertiary teaching hospital.
Clinics (Sao Paulo, Brazil)
Oct 9, 2024
BACKGROUND: Hepatocellular carcinoma (HCC) is a prevalent tumor with high mortality rates. Computed tomography (CT) is crucial in the non-invasive diagnosis of HCC. Recent advancements in artificial intelligence (AI) have shown significant potential ...
Machine learning-based identification and validation of aging-related genes in cardiomyocytes from patients with atrial fibrillation.
Minerva cardiology and angiology
Oct 8, 2024
BACKGROUND: Aging is a key risk factor for atrial fibrillation (AF), a prevalent cardiac disorder among the elderly. This study aims to elucidate the genetic underpinnings of AF in the context of aging.
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