AIMC Topic: Middle Aged

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Survey on Value Elements Provided by Artificial Intelligence and Their Eligibility for Insurance Coverage With an Emphasis on Patient-Centered Outcomes.

Korean journal of radiology
OBJECTIVE: This study aims to explore the opinions on the insurance coverage of artificial intelligence (AI), as categorized based on the distinct value elements offered by AI, with a specific focus on patient-centered outcomes (PCOs). PCOs are disti...

Predictive analytics for cardiovascular patient readmission and mortality: An explainable approach.

Computers in biology and medicine
BACKGROUND: Cardiovascular patients experience high rates of adverse outcomes following discharge from hospital, which may be preventable through early identification and targeted action. This study aimed to investigate the effectiveness and explaina...

Predicting the Severity and Discharge Prognosis of Traumatic Brain Injury Based on Intracranial Pressure Data Using Machine Learning Algorithms.

World neurosurgery
OBJECTIVE: This study aimed to explore the potential of employing machine learning algorithms based on intracranial pressure (ICP), ICP-derived parameters, and their complexity to predict the severity and short-term prognosis of traumatic brain injur...

Correlating Age and Hematoma Volume with Extent of Midline Shift in Acute Subdural Hematoma Patients: Validation of an Artificial Intelligence Tool for Volumetric Analysis.

World neurosurgery
OBJECTIVE: Decision for intervention in acute subdural hematoma patients is based on a combination of clinical and radiographic factors. Age has been suggested as a factor to be strongly considered when interpreting midline shift (MLS) and hematoma v...

Distribution and determinants of choroidal vascularity index in healthy eyes from deep-learning choroidal analysis: a population-based SS-OCT study.

The British journal of ophthalmology
AIMS: To quantify the profiles of choroidal vascularity index (CVI) using fully artificial intelligence (AI)-based algorithm applied to swept-source optical coherence tomography (SS-OCT) images and evaluate the determinants of CVI in a population-bas...

A deep learning method to identify and localize large-vessel occlusions from cerebral digital subtraction angiography.

Journal of neuroimaging : official journal of the American Society of Neuroimaging
BACKGROUND AND PURPOSE: An essential step during endovascular thrombectomy is identifying the occluded arterial vessel on a cerebral digital subtraction angiogram (DSA). We developed an algorithm that can detect and localize the position of occlusion...

Exploring the Low-Dose Limit for Focal Hepatic Lesion Detection with a Deep Learning-Based CT Reconstruction Algorithm: A Simulation Study on Patient Images.

Journal of imaging informatics in medicine
This study aims to investigate the maximum achievable dose reduction for applying a new deep learning-based reconstruction algorithm, namely the artificial intelligence iterative reconstruction (AIIR), in computed tomography (CT) for hepatic lesion d...

Machine learning models for classifying non-specific neck pain using craniocervical posture and movement.

Musculoskeletal science & practice
OBJECTIVE: Physical therapists and clinicians commonly confirm craniocervical posture (CCP), cervical retraction, and craniocervical flexion as screening tests because they contribute to non-specific neck pain (NSNP). We compared the predictive perfo...

Practical use case of natural language processing for observational clinical research data retrieval from electronic health records: AssistMED project.

Polish archives of internal medicine
INTRODUCTION: Electronic health records (EHRs) contain data valuable for clinical research. However, they are in textual format and require manual encoding to databases, which is a lengthy and costly process. Natural language processing (NLP) is a co...