AIMC Topic: Middle Aged

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Predicting the risk of postoperative constipation in middle-aged and elderly patients with lower limb fractures using machine learning algorithms.

PloS one
OBJECTIVE: To construct and validate a predictive model for the risk of postoperative constipation in middle-aged and elderly patients with lower limb fractures based on machine learning algorithms, so as to provide decision-making support for clinic...

Data-driven cluster analysis identifies three clinical phenotypes in hemodialysis patients.

Renal failure
Clinical heterogeneity among hemodialysis patients necessitates precision medicine approaches transcending conventional single-parameter management. Through machine learning analysis of 1,207 maintenance hemodialysis patients, we developed a novel tw...

Earlier prediction of Parkinson's disease using cross non-decimated wavelet transform and machine learning algorithm.

Scientific reports
Parkinson's disease (PD) is a brain disorder, that affects a person's body movement causing stiffness, shaking and imbalance. Earlier detection of PD is a challenging task for researchers. In this paper, earlier detection of PD is performed using the...

A novel approach of developing machine learning based models for the prediction of facial dimensions from dental parameters.

Scientific reports
Personal identification of an individual has always been a major concern in forensic science. Reconstruction of the facial profile is considered as one of the final stages in the process of identification. Nevertheless, recent advancements in artific...

Predicting proximal junctional failure in adult spinal deformity patients using machine learning models based on spinal alignment parameters.

Scientific reports
Proximal junctional failure (PJF) is a significant mechanical complication following corrective surgery for adult spinal deformity (ASD), often resulting in structural failure at the uppermost instrumented vertebra and necessitating revision surgery....

AI-driven clinical decision support for early diagnosis and treatment planning in patients with suspected sleep apnea using clinical and demographic data before sleep studies.

NPJ primary care respiratory medicine
OBJECTIVE: This study explored the application of Machine Learning (ML) techniques to cluster patients with suspected sleep apnea (SA), based on clinical-demographic data, with the aim of optimizing diagnostic pathways and enabling more personalized ...

Macrophage mitophagy-related genes predict prognosis and therapeutic response in lung adenocarcinoma.

Scientific reports
Mitochondrial autophagy (mitophagy) in macrophages is crucial yet poorly understood within the lung adenocarcinoma (LUAD) tumor microenvironment. This study aimed to identify key macrophage mitophagy-related genes and develop a robust prognostic mode...

Face2Bone explainable AI model predicts osteoporosis risk from facial images in proof of concept study.

Scientific reports
OBJECTIVES: BMI and age are associated with the risk of osteoporosis (OP). The dynamic facial aging process involves changes in skin, muscle, fat, and facial bone structures, with facial skeletal aging affecting facial contours through volumetric red...

IGFBP7 and CCT2 are novel lactylation-driven mediators of endothelial-to-mesenchymal transition in idiopathic pulmonary fibrosis.

Functional & integrative genomics
Lactylation is a post-translational modification that can influence the onset and progression of various diseases.However, its role in Idiopathic Pulmonary Fibrosis (IPF) has not been systematically investigated. Single-cell sequencing and bulk RNA s...

A machine learning-enhanced gastric cancer diagnostic method based on shell-isolated nanoparticle-enhanced Raman spectroscopy.

Nanoscale
Gastric cancer (GC) remains one of the most prevalent and lethal malignancies worldwide, necessitating the development of efficient, non-invasive methods for early detection. In this study, a serum diagnostic approach based on shell-isolated nanopart...