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Dynamic Lymphocyte Recovery Patterns Predict 90-Day Mortality in Sepsis: A Machine Learning-Enhanced Analysis of the MIMIC-IV Cohort

Sepsis-induced immunosuppression, characterized by lymphopenia, is associated with adverse outcomes....

Precision Immunosuppression and Long-Term Kidney Transplant Outcomes: A Dual Survival Modeling Framework

Optimizing immunosuppressive therapy remains central to improving long-term outcomes after kidney tr...

Exploring the Mechanisms of Sanguinarine in the Treatment of Osteoporosis by Integrating Network Pharmacology Analysis and Deep Learning Technology.

BACKGROUND: Sanguinarine (SAN) has been reported to have antioxidant, antiinflammatory, and antimicr...

Jan 2025 38385487
DeepTransformer: Node Classification Research of a Deep Graph Network on an Osteoporosis Graph based on GraphTransformer.

BACKGROUND: Osteoporosis (OP) is one of the most common diseases in the elderly population. It is mo...

Jan 2025 39651564
Diagnosis Osteoporosis Risk: Using Machine Learning Algorithms Among Fasa Adults Cohort Study (FACS).

INTRODUCTION: In Iran, the assessment of osteoporosis through tools like dual-energy X-ray absorptio...

Jan 2025 39760233
Bayesian-optimized deep learning for identifying essential genes of mitophagy and fostering therapies to combat drug resistance in human cancers.

Dysregulated mitophagy is essential for mitochondrial quality control within human cancers. However,...

Jan 2025 39834330
An Intrinsically Explainable Approach to Detecting Vertebral Compression Fractures in CT Scans via Neurosymbolic Modeling

Vertebral compression fractures (VCFs) are a common and potentially serious consequence of osteopo...

Computer-Aided Osteoporosis Diagnosis Using Transfer Learning with Enhanced Features from Stacked Deep Learning Modules

Knee osteoporosis weakens the bone tissue in the knee joint, increasing fracture risk. Early detec...

Osteoporosis Prediction from Hand X-ray Images Using Segmentation-for-Classification and Self-Supervised Learning

Osteoporosis is a widespread and chronic metabolic bone disease that often remains undiagnosed and...

Incorporating Metabolic Information into LLMs for Anomaly Detection in Clinical Time-Series

Anomaly detection in clinical time-series holds significant potential in identifying suspicious pa...

Identification of novel M2 macrophage-related molecule ATP6V1E1 and its biological role in hepatocellular carcinoma based on machine learning algorithms.

Hepatocellular carcinoma (HCC) remains the most prevalent form of primary liver cancer, characterize...

Sep 2024 39294741
Vertebral compression fractures at abdominal CT: underdiagnosis, undertreatment, and evaluation of an AI algorithm.

Vertebral compression fractures (VCFs) are common and indicate a high future risk of additional oste...

Aug 2024 38900913
Can we screen opportunistically for low bone mineral density using CT scans of the shoulder and artificial intelligence?

OBJECTIVE: To evaluate whether the CT attenuation of bones seen on shoulder CT scans could be used t...

Aug 2024 38837337
Predicting the role of the human gut microbiome in type 1 diabetes using machine-learning methods.

Gut microbes is a crucial factor in the pathogenesis of type 1 diabetes (T1D). However, it is still ...

Jul 2024 38376798
DP2LM: leveraging deep learning approach for estimation and hypothesis testing on mediation effects with high-dimensional mediators and complex confounders.

Traditional linear mediation analysis has inherent limitations when it comes to handling high-dimens...

Jul 2024 38330064
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