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Age Factors

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Predicting rapid progression in knee osteoarthritis: a novel and interpretable automated machine learning approach, with specific focus on young patients and early disease.

Annals of the rheumatic diseases
OBJECTIVES: To facilitate the stratification of patients with osteoarthritis (OA) for new treatment development and clinical trial recruitment, we created an automated machine learning (autoML) tool predicting the rapid progression of knee OA over a ...

Predictive modeling with linear machine learning can estimate glioblastoma survival in months based solely on MGMT-methylation status, age and sex.

Acta neurochirurgica
PURPOSE: Machine Learning (ML) has become an essential tool for analyzing biomedical data, facilitating the prediction of treatment outcomes and patient survival. However, the effectiveness of ML models heavily relies on both the choice of algorithms...

Analyzing patterns of frequent mental distress in Alzheimer's patients: A generative AI approach.

Journal of the National Medical Association
This study tackles creating Python code for beginners with generative AI and analyzing trends in mental distress among Alzheimer's patients in the US (2015-2022 CDC data). It guides beginners through using AI to generate code for visualizing these tr...

Associations between age, red cell distribution width and 180-day and 1-year mortality in giant cell arteritis patients: mediation analyses and machine learning in a cohort study.

Arthritis research & therapy
OBJECTIVE: The aim of this study was to investigate the correlation between age, red cell distribution width (RDW) levels, and 180-day and 1-year mortality in giant cell arteritis (GCA) patients hospitalized or admitted to the ICU.

A Meta-Analysis of Artificial Intelligence Technologies Use and Loneliness: Examining the Influence of Physical Embodiment, Age Differences, and Effect Direction.

Cyberpsychology, behavior and social networking
Recent research has investigated the connection between artificial intelligence (AI) utilization and feelings of loneliness, yielding inconsistent outcomes. This meta-analysis aims to clarify this relationship by synthesizing data from 47 relevant st...

Age and gender-related changes in choroidal thickness: Insights from deep learning analysis of swept-source OCT images.

Photodiagnosis and photodynamic therapy
BACKGROUND: The choroid is a vital vascular layer of the eye, essential for maintaining ocular health. Understanding its structural variations, particularly choroidal thickness (CT), is crucial for the early detection of diseases, such as age-related...

Conventional and machine learning-based analysis of age, body weight and body height significance in knot position-related thyrohyoid and cervical spine fractures in suicidal hangings.

International journal of legal medicine
The thyrohyoid complex and cervical spine fracture distribution patterns may reflect the knot position as the force distribution by the noose to different neck regions may vary depending on it. Recently, machine learning models (MLm) were used to cla...

Cold storage surpasses the impact of biological age and donor characteristics on red blood cell morphology classified by deep machine learning.

Scientific reports
Assessment of the morphology of red blood cells (RBCs) can improve clinical benefits following blood transfusion. Deep machine learning surpasses traditional microscopy-based classification methods, offering more accurate and consistent results while...

Effects of artificial intelligence and virtual reality interventions in art therapy among older people with mild cognitive impairment.

Australasian journal on ageing
OBJECTIVES: Integrating artificial intelligence and virtual reality into an art health program, this study aimed to compare the effects of artificial intelligence (AI) intervention in art therapy, virtual reality (VR) intervention in art therapy and ...

Determinants of ascending aortic morphology: cross-sectional deep learning-based analysis on 25 073 non-contrast-enhanced NAKO MRI studies.

European heart journal. Cardiovascular Imaging
AIMS: Understanding determinants of thoracic aortic morphology is crucial for precise diagnostics and therapeutic approaches. This study aimed to automatically characterize ascending aortic morphology based on 3D non-contrast-enhanced magnetic resona...