AIMC Topic: Machine Learning

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Exploring the effect of the triglyceride-glucose index on bone metabolism in prepubertal children, a retrospective study: insights from traditional methods and machine-learning-based bone remodeling prediction.

PeerJ
BACKGROUND: Childhood obesity poses a significant risk to bone health, but the impact of insulin resistance (IR) on bone metabolism in prepubertal children, as assessed by the triglyceride-glucose (TyG) index, remains underexplored. Bone turnover mar...

Interpretable noninvasive diagnosis of tuberculous pleural effusion using LGBM and SHAP: development and clinical application of a machine learning model.

PeerJ
BACKGROUND: Tuberculous pleural effusion (TPE) is a prevalent tuberculosis complication, with diagnosis presenting considerable challenges. Timely and precise identification of TPE is vital for effective patient management and prognosis, yet existing...

Transfer learning for mortality risk: A case study on the United Kingdom.

PloS one
This study introduces a transfer learning framework to address data scarcity in mortality risk prediction for the UK, where local mortality data is unavailable. By leveraging a pretrained model built from data across eight countries (excluding the UK...

Recent progress in tuberculosis diagnosis: insights into blood-based biomarkers and emerging technologies.

Frontiers in cellular and infection microbiology
Tuberculosis (TB) remains a global health challenge, with timely and accurate diagnosis being critical for effective disease management and control. Recent advancements in the field of TB diagnostics have focused on the identification and utilization...

Personalized treatment decision-making using a machine learning-derived lactylation signature for breast cancer prognosis.

Frontiers in immunology
BACKGROUND: Breast cancer is a heterogeneous malignancy with complex molecular characteristics, making accurate prognostication and treatment stratification particularly challenging. Emerging evidence suggests that lactylation, a novel post-translati...

Identification and validation of shared biomarkers and drug repurposing in psoriasis and Crohn's disease: integrating bioinformatics, machine learning, and experimental approaches.

Frontiers in immunology
BACKGROUND: Psoriasis and Crohn's disease (CD) are chronic inflammatory diseases that involve complex immune-mediated mechanisms. Despite clinical overlap and shared genetic predispositions, the molecular pathways connecting these diseases remain inc...

Identification of regulatory cell death-related genes during MASH progression using bioinformatics analysis and machine learning strategies.

Frontiers in immunology
BACKGROUND: Metabolic dysfunction-associated steatohepatitis (MASH) is becoming increasingly prevalent. Regulated cell death (RCD) has emerged as a significant disease phenotype and may act as a marker for liver fibrosis. The present study aimed to i...

Identification and validation of immune-related and inflammation-related genes in endometriosis.

Frontiers in endocrinology
AIM: Endometriosis is characterized by immune evasion and progressive inflammation. This study aimed to identify key genes related to immune and inflammation in endometriosis.

Research on the financial early warning models based on ensemble learning algorithms: Introducing MD&A and stock forum comments textual indicators.

PloS one
This study analyzes 284 publicly listed companies first designated as ST or *ST between 2015 and 2023. It utilizes two types of textual indicators: Management's Discussion and Analysis (MD&A) and stock forum comments. PCA and MLP are employed for dim...

A Real-Time Plasma Concentration Prediction Model for Voriconazole in Elderly Patients via Machine Learning Combined with Population Pharmacokinetics.

Drug design, development and therapy
PURPOSE: Voriconazole (VCZ) is a first-line treatment for invasive fungal disease, characterized by a narrow therapeutic window and significant inter-individual variability. It is primarily metabolized by the liver, the function of which declines wit...