AIMC Topic: Aged

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Faster Acquisition and Improved Image Quality of T2-Weighted Dixon Breast MRI at 3T Using Deep Learning: A Prospective Study.

Korean journal of radiology
OBJECTIVE: The aim of this study was to compare image quality features and lesion characteristics between a faster deep learning (DL) reconstructed T2-weighted (T2-w) fast spin-echo (FSE) Dixon sequence with super-resolution (T2) and a conventional T...

Using voice recognition and machine learning techniques for detecting patient-reported outcomes from conversational voice in palliative care patients.

Japan journal of nursing science : JJNS
AIM: Patient-reported outcome measures (PROMs) are increasingly used in palliative care to evaluate patients' symptoms and conditions. Healthcare providers often collect PROMs through conversations. However, the manual entry of these data into electr...

Prediction of Cisplatin-Induced Acute Kidney Injury Using an Interpretable Machine Learning Model and Electronic Medical Record Information.

Clinical and translational science
Predicting cisplatin-induced acute kidney injury (Cis-AKI) before its onset is important. We aimed to develop a predictive model for Cis-AKI using patient clinical information based on an interpretable machine learning algorithm. This single-center r...

Diagnosis Osteoporosis Risk: Using Machine Learning Algorithms Among Fasa Adults Cohort Study (FACS).

Endocrinology, diabetes & metabolism
INTRODUCTION: In Iran, the assessment of osteoporosis through tools like dual-energy X-ray absorptiometry poses significant challenges due to their high costs and limited availability, particularly in small cities and rural areas. Our objective was t...

Point-of-Care Potassium Measurement vs Artificial Intelligence-Enabled Electrocardiography for Hyperkalemia Detection.

American journal of critical care : an official publication, American Association of Critical-Care Nurses
BACKGROUND: Hyperkalemia can be detected by point-of-care (POC) blood testing and by artificial intelligence- enabled electrocardiography (ECG). These 2 methods of detecting hyperkalemia have not been compared.

Use of Machine Learning Models to Predict Microaspiration Measured by Tracheal Pepsin A.

American journal of critical care : an official publication, American Association of Critical-Care Nurses
BACKGROUND: Enteral feeding intolerance, a common type of gastrointestinal dysfunction leading to underfeeding, is associated with increased mortality. Tracheal pepsin A, an indicator of microaspiration, was found in 39% of patients within 24 hours o...

Artificial Intelligence Models Could Enhance the Diagnostic Accuracy (DA) of Fecal Immunochemical Test (FIT) in the Detection of Colorectal Adenoma in a Screening Setting.

Anticancer research
BACKGROUND/AIM: This study evaluated the diagnostic accuracy (DA) for colorectal adenomas (CRA), screened by fecal immunochemical test (FIT), using five artificial intelligence (AI) models: logistic regression (LR), support vector machine (SVM), neur...

Deep Learning-Based Prediction of Freezing of Gait in Parkinson's Disease With the Ensemble Channel Selection Approach.

Brain and behavior
PURPOSE: A debilitating and poorly understood symptom of Parkinson's disease (PD) is freezing of gait (FoG), which increases the risk of falling. Clinical evaluations of FoG, relying on patients' subjective reports and manual examinations by speciali...

World-making for a future with sentient AI.

The British journal of social psychology
The ways people imagine possible futures with artificial intelligence (AI) affects future world-making-how the future is produced through cultural propagation, design, engineering, policy, and social interaction-yet there has been little empirical st...

A Machine Learning Model to Harmonize Volumetric Brain MRI Data for Quantitative Neuroradiologic Assessment of Alzheimer Disease.

Radiology. Artificial intelligence
Purpose To extend a previously developed machine learning algorithm for harmonizing brain volumetric data of individuals undergoing neuroradiologic assessment of Alzheimer disease not encountered during model training. Materials and Methods Neuroharm...