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Machine Learning - AI Medical Compendium

AIMC Topic: Machine Learning

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A Machine Learning Model for Predicting Sarcopenia Among Middle-Aged Adults: Development and External Validation.

JMIR medical informatics Aug 27, 2025
BACKGROUND: Sarcopenia is a common muscle disorder in older adults, and its early identification and management in middle-aged populations are essential for ensuring a healthier later life. Detecting sarcopenia at an earlier stage may reduce the futu...
Humans Adult Male Middle Aged Nutrition Surveys Machine Learning Republic of Korea Female Hand Strength Sarcopenia
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MRI-based machine-learning radiomics of the liver to predict liver-related events in hepatitis B virus-associated fibrosis.

European radiology experimental Aug 27, 2025
BACKGROUND: The onset of liver-related events (LREs) in fibrosis indicates a poor prognosis and worsens patients' quality of life, making the prediction and early detection of LREs crucial. The aim of this study was to develop a radiomics model using...
Radiomics Machine Learning Female Male Liver Cirrhosis Middle Aged Adult Humans Magnetic Resonance Imaging Hepatitis B, Chronic
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Machine learning-based models and radiomics: can they be reliable predictors for meningioma recurrence? A systematic review and meta-analysis.

Neurosurgical review Aug 27, 2025
BACKGROUND: Predicting recurrence in meningioma patients is vital for improving long-term outcomes and tailoring personalized treatment strategies. While traditional diagnostic methods have advanced, accurately forecasting recurrence remains a persis...
Neoplasm Recurrence, Local Meningioma Meningeal Neoplasms Humans Machine Learning Radiomics
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From pixels to patterns: Coupling Optical Coherence Tomography and machine learning for monitoring coastal wetland root systems.

The Science of the total environment Aug 26, 2025
Coastal wetlands are crucial in shoreline stabilization, carbon sequestration, and storm protection. Yet, due to limitations in traditional destructive sampling techniques, the belowground biomass (live root mass) and necromass (dead and decaying roo...
Plant Roots Tomography, Optical Coherence Wetlands Louisiana Machine Learning Biomass Environmental Monitoring
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Predicting children and adolescents at high risk of poor health‑related quality of life using machine learning methods.

Health and quality of life outcomes Aug 26, 2025
BACKGROUND: Existing research has identified health‑related quality of life (HRQoL) is influenced by a multitude of factors among children and adolescents. However, there has been relatively limited exploration of the multidimensional predictive fact...
Adolescent Male Child Nomograms Quality of Life Logistic Models Humans Surveys and Questionnaires Machine Learning Female
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Machine Learning-Driven radiomics on 18 F-FDG PET for glioma diagnosis: a systematic review and meta-analysis.

Cancer imaging : the official publication of the International Cancer Imaging Society Aug 26, 2025
BACKGROUND: Machine learning (ML) applied to radiomics has revolutionized neuro-oncological imaging, yet the diagnostic performance of ML models based specifically on ^18F-FDG PET features in glioma remains poorly characterized.
Radiopharmaceuticals Positron-Emission Tomography Fluorodeoxyglucose F18 Radiomics Brain Neoplasms Glioma Humans Machine Learning
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Explainable machine learning identifies key quality-of-life-related predictors of arthritis status: evidence from the China health and retirement longitudinal study.

Health and quality of life outcomes Aug 26, 2025
BACKGROUND: Arthritis is a prevalent chronic disease substantially impacting patients' quality of life (QoL). While identifying key determinants associated with arthritis is critical for targeted interventions, traditional statistical methods often s...
China Longitudinal Studies Arthritis Aged Male Humans Middle Aged Machine Learning Quality of Life Female
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ADAMTS2 mediates epithelial‒mesenchymal transition and inflammation in high-grade serous ovarian cancer: a study based on bioinformatic analyses and experiments.

BMC cancer Aug 26, 2025
BACKGROUND: The importance of epithelial‒mesenchymal transition (EMT) in tumour invasion and metastasis in high-grade serous ovarian cancer (HGSOC) has been highlighted in numerous studies, but genetic biomarkers for predicting EMT in HGSOC are still...
Female Tumor Microenvironment Cystadenocarcinoma, Serous Biomarkers, Tumor Middle Aged Ovarian Neoplasms Humans Gene Expression Regulation, Neoplastic Cell Line, Tumor Machine Learning Epithelial-Mesenchymal Transition Inflammation Computational Biology Prognosis ADAMTS Proteins Cell Movement
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Exploring the potential relationship between kidney disease index and cognitive dysfunction: a machine learning approach with NHANES data.

BMC geriatrics Aug 26, 2025
OBJECTIVE: This study investigates the relationship between the Kidney Disease Index (KDI) and cognitive function, evaluating its potential as a predictive marker for cognitive impairment in older adults. We also compare the performance of KDI with t...
Creatinine Humans Machine Learning Nutrition Surveys Aged, 80 and over Glomerular Filtration Rate Cross-Sectional Studies Male Kidney Diseases Female Middle Aged Aged Cognitive Dysfunction
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Screening of hub genes and immunocytes related to tendon injury based on bioinformatics and machine learning models.

Scientific reports Aug 26, 2025
Tendon injury is a common and challenging clinical problem, and its healing process involves complex cellular and biological factors. Therefore, this study aims to reveal the mechanism of tendon healing and provide theoretical basis for clinical trea...
Databases, Genetic Tendon Injuries Gene Regulatory Networks Computational Biology Signal Transduction Humans Machine Learning Macrophages Gene Expression Profiling Protein Interaction Maps
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