AIMC Topic: Aged
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Employing a low-code machine learning approach to predict in-hospital mortality and length of stay in patients with community-acquired pneumonia.
Scientific reports
Jan 2, 2025
Community-acquired pneumonia (CAP) is associated with high mortality rates and often results in prolonged hospital stays. The potential of machine learning to enhance prediction accuracy in this context is significant, yet clinicians often lack the p...
Deep learning and genome-wide association meta-analyses of bone marrow adiposity in the UK Biobank.
Nature communications
Jan 2, 2025
Bone marrow adipose tissue is a distinct adipose subtype comprising more than 10% of fat mass in healthy humans. However, the functions and pathophysiological correlates of this tissue are unclear, and its genetic determinants remain unknown. Here, w...
Machine learning for early detection and severity classification in people with Parkinson's disease.
Scientific reports
Jan 2, 2025
Early detection of Parkinson's disease (PD) and accurate assessment of disease progression are critical for optimizing treatment and rehabilitation. However, there is no consensus on how to effectively detect early-stage PD and classify motor symptom...
Validation of musculoskeletal segmentation model with uncertainty estimation for bone and muscle assessment in hip-to-knee clinical CT images.
Scientific reports
Jan 2, 2025
Deep learning-based image segmentation has allowed for the fully automated, accurate, and rapid analysis of musculoskeletal (MSK) structures from medical images. However, current approaches were either applied only to 2D cross-sectional images, addre...
Machine learning derived retinal pigment score from ophthalmic imaging shows ethnicity is not biology.
Nature communications
Jan 2, 2025
Few metrics exist to describe phenotypic diversity within ophthalmic imaging datasets, with researchers often using ethnicity as a surrogate marker for biological variability. We derived a continuous, measured metric, the retinal pigment score (RPS),...
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
Jan 2, 2025
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 ...
Identification of key gene signatures for predicting chemo-immunotherapy efficacy in extensive-stage small-cell lung cancer using machine learning.
Lung cancer (Amsterdam, Netherlands)
Jan 2, 2025
OBJECTIVES: The lack of definitive biomarkers presents a significant challenge for chemo-immunotherapy in extensive-stage small-cell lung cancer (ES-SCLC). We aimed to identify key genes associated with chemo-immunotherapy efficacy in ES-SCLC through...
Treatment Outcome
Prospective Studies
Neoplasm Staging
Prognosis
Small Cell Lung Carcinoma
Female
Lung Neoplasms
Aged
Immunotherapy
Biomarkers, Tumor
Gene Expression Regulation, Neoplastic
Male
Antineoplastic Combined Chemotherapy Protocols
Humans
Middle Aged
Machine Learning
Gene Expression Profiling
Transcriptome
International multicenter validation of AI-driven ultrasound detection of ovarian cancer.
Nature medicine
Jan 2, 2025
Ovarian lesions are common and often incidentally detected. A critical shortage of expert ultrasound examiners has raised concerns of unnecessary interventions and delayed cancer diagnoses. Deep learning has shown promising results in the detection o...
Multi-Modal Diagnosis of Alzheimer's Disease Using Interpretable Graph Convolutional Networks.
IEEE transactions on medical imaging
Jan 2, 2025
The interconnection between brain regions in neurological disease encodes vital information for the advancement of biomarkers and diagnostics. Although graph convolutional networks are widely applied for discovering brain connection patterns that poi...
Iodine Density of Lymphoma, Metastatic SCCA, and Normal Cervical lymph nodes: A Comparative Analysis Based on DLSCT.
F1000Research
Jan 2, 2025
OBJECTIVE: To compare iodine density (ID) and contrast-enhanced attenuation value (CEAV) from dual-layer spectral computed tomography (DLSCT) scans of lymphomatous, metastatic squamous cell carcinoma (SCCA), and normal cervical lymph nodes.
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