AIMC Topic: Prognosis

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Development and validation of a machine learning model for predicting vulnerable carotid plaques using routine blood biomarkers and derived indicators: insights into sex-related risk patterns.

Cardiovascular diabetology
BACKGROUND: Early detection of vulnerable carotid plaques is critical for stroke prevention. This study aimed to develop a machine learning model based on routine blood tests and derived indices to predict plaque vulnerability and assess sex-specific...

Multi-omics insights of immune cells in the risk and prognosis of idiopathic membranous nephropathy.

Communications biology
Idiopathic membranous nephropathy (IMN) is the major cause of autoimmune-related nephrotic syndrome. The role immune cells play in the risk and prognosis of IMN remains elusive. We employ multi-omics data and a variety of approaches to evaluate the c...

AI-driven multi-modal framework for prognostic modeling in glioblastoma: Enhancing clinical decision support.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
OBJECTIVE: Glioblastoma (GBM) is the most aggressive malignant brain tumor, associated with poor prognosis and limited therapeutic options. Accurate prognostic modeling is essential for guiding personalized treatment strategies. However, existing mod...

Machine learning derived development and validation of extracellular matrix related signature for predicting prognosis in adolescents and young adults glioma.

Scientific reports
The mortality rates have been increasing for glioma in adolescents and young adults (AYAs, aged 15-39 years). However, current biomarkers for clinical assessment in AYAs glioma are limited, prompting the urgent need for identifying ideal prognostic s...

Multi-modal machine learning classifier for idiopathic pulmonary fibrosis predicts mortality in interstitial lung diseases.

Respiratory investigation
BACKGROUND: Interstitial lung disease (ILD) prognostication incorporates clinical history, pulmonary function testing (PFTs), and chest CT pattern classifications. The machine learning classifier, Fibresolve, includes a model to help detect CT patter...

Incorporation of Metabolic Dysfunction-Associated Steatotic Liver Disease in the Health Stage of Cardiovascular-Kidney-Metabolic Syndrome Improves Predictive Ability for Coronary Artery Disease in a Japanese General Population.

Journal of the American Heart Association
BACKGROUND: Cardiovascular-kidney-metabolic (CKM) syndrome is a recently proposed condition encompassing metabolic dysfunction, chronic kidney disease, and cardiovascular diseases including coronary artery disease (CAD). Although concomitant metaboli...

A Machine Learning-Based Prognostication Model Enhances Prediction of Early Hepatic Encephalopathy in Patients With Noncancer-Related Cirrhosis: Multicenter Longitudinal Cohort Study in Taiwan.

JMIR medical informatics
BACKGROUND: Hepatic encephalopathy (HE) contributes significantly to mortality among patients with liver cirrhosis. Early prediction of HE is essential for clinical decision-making, yet remains challenging-particularly in noncancer-related cirrhosis ...

The relationship between clinical subtypes, prognosis, and treatment in ICU patients with acute cholangitis using unsupervised machine learning methods.

BMC infectious diseases
BACKGROUND: Acute cholangitis (AC) presents with significant clinical heterogeneity, and existing severity classifications have limited prognostic value in critically ill patients. Subtypes of AC in critically ill patients have not been investigated.

Integrated multiple machine learning and Mendelian randomization reveal LTF gene as a prognostic biomarker for nonspecific orbital inflammation.

BMC pharmacology & toxicology
BACKGROUND: Nonspecific orbital inflammation (NSOI), also known as idiopathic orbital inflammation, comprises a heterogeneous group of immune-mediated disorders affecting orbital tissues, unified by the absence of a defined etiology. Lactotransferrin...