AIMC Topic: Aged

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Metagenomic next-generation sequencing unraveled the characteristic of lung microbiota in patients with checkpoint inhibitor pneumonitis: results from a prospective cohort study.

Journal for immunotherapy of cancer
BACKGROUND: Checkpoint inhibitor pneumonitis (CIP) is among the most lethal immune-related adverse events in patients with cancer receiving immunotherapy. This study aims to characterize the lung microbiome in patients with CIP and evaluate its diagn...

Development and validation of a predictive model for adherent perirenal fat based on CT radiomics and deep learning.

World journal of urology
PURPOSE: The study aimed to develop and validate a predictive model for preoperative APF using computed tomography (CT) radiomics combined with deep learning, and validating the performance of the model in an independent cohort.

AI-based HRCT quantification reveals DLCO and TLC as key determinants of ILD severity in connective tissue diseases.

RMD open
OBJECTIVE: Interstitial lung disease (ILD) represents the most common and severe organ manifestation observed in patients diagnosed with connective tissue diseases (CTDs). The aim of this retrospective cross-sectional study was to identify clinical r...

Brain-derived 5-hydroxymethylcytosine epigenetic scores are related to Alzheimer's disease pathology and cognitive decline.

Acta neuropathologica
BACKGROUND: Cytosine modifications play critical roles in gene regulation and disease pathogenesis. Elucidating novel epigenetic contributions to Alzheimer's disease (AD) could advance diagnostic, prognostic, and therapeutic strategies. 5-hydroxymeth...

Can machine learning improve on the early prediction of upper limb recovery after stroke?

Journal of neuroengineering and rehabilitation
BACKGROUND: Early prediction of upper limb recovery is important to optimise rehabilitation and inform patients but remains challenging due to inter-individual variability. This study aims to (1) develop and validate a machine learning model to predi...

Integrating deep learning and multi-omics features in radiation pneumonitis prediction for lung cancer patients using PET/CT.

BMC medical imaging
BACKGROUND: To investigate the feasibility and accuracy of PET radiomics features, along with their combination with CT radiomics, dosiomics, and deep learning (DL) features, in predicting radiation pneumonitis (RP) in lung cancer patients treated wi...

The prognostic value of POD24 for multiple myeloma: a comprehensive analysis based on traditional statistics and machine learning.

BMC cancer
BACKGROUND: In multiple myeloma, progression within 24 months (POD24) is a strong adverse prognostic factor. However, its impact on overall survival (OS) remains underexplored through machine learning.

The effect of kinesiophobia and successful aging on quality of life in older adults: machine learning approach.

BMC geriatrics
BACKGROUND: Kinesiophobia and successful aging are key factors affecting quality of life in older adults; kinesiophobia, the fear of movement, can lead to reduced physical activity, while successful aging promotes overall well-being.

Using unsupervised machine learning methods to cluster cardio-metabolic profile of the middle-aged and elderly Chinese with general and central obesity.

BMC cardiovascular disorders
BACKGROUND: Obesity is a disease with high heterogeneity. Both overall obesity and central obesity are associated with increased risks of having cardio-metabolic co-morbidities. This study is aimed to examine the cardio-metabolic characteristics and ...