AIMC Topic: Disease Progression

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Predicting knee osteoarthritis progression using neural network with longitudinal MRI radiomics, and biochemical biomarkers: A modeling study.

PLoS medicine
BACKGROUND: Knee osteoarthritis (KOA) worsens both structurally and symptomatically, yet no model predicts KOA progression using Magnetic Resonance Image (MRI) radiomics and biomarkers. This study aimed to develop and test the longitudinal Load-Beari...

Advancements and challenges in pediatric dilated cardiomyopathy: a comprehensive review of current approaches and future directions.

European journal of pediatrics
Cardiomyopathies pose a significant risk of morbidity and mortality worldwide, with dilated cardiomyopathy (DCM) recognized as the leading cause of pediatric heart transplantation. Understanding the unique presentation of DCM in the pediatric populat...

Longitudinal structural MRI-based deep learning and radiomics features for predicting Alzheimer's disease progression.

Alzheimer's research & therapy
BACKGROUND: Alzheimer's disease (AD) is the principal cause of dementia and requires the early diagnosis of people with mild cognitive impairment (MCI) who are at high risk of progressing. Early diagnosis is imperative for optimizing clinical managem...

Urinary Complement proteome strongly linked to diabetic kidney disease progression.

Nature communications
Diabetic kidney disease (DKD) progression is not well understood. Using high-throughput proteomics, biostatistical, pathway and machine learning tools, we examine the urinary Complement proteome in two prospective cohorts with type 1 or 2 diabetes an...

Alzheimer's disease risk prediction using machine learning for survival analysis with a comorbidity-based approach.

Scientific reports
Alzheimer's disease (AD) presents a pressing global health challenge, demanding improved strategies for early detection and understanding its progression. In this study, we address this need by employing survival analysis techniques to predict transi...

Predictive Modeling of Osteonecrosis of the Femoral Head Progression Using MobileNetV3_Large and Long Short-Term Memory Network: Novel Approach.

JMIR medical informatics
BACKGROUND: The assessment of osteonecrosis of the femoral head (ONFH) often presents challenges in accuracy and efficiency. Traditional methods rely on imaging studies and clinical judgment, prompting the need for advanced approaches. This study aim...

Artificial intelligence algorithms for differentiating pseudoprogression from true progression in high-grade gliomas: A systematic review and meta-analysis.

Neurosurgical review
Differentiating pseudoprogression (PsP) from true progression (TP) in high-grade glioma (HGG) patients is still challenging and critical for effective treatment management. This meta-analysis evaluates the diagnostic accuracy of artificial intelligen...

Initiation of antifibrotic treatment in fibrosing interstitial lung disease: is the clock ticking till proven progression?

European respiratory review : an official journal of the European Respiratory Society
Several interstitial lung diseases (ILDs) with different aetiologies and pathogenic mechanisms may exhibit a progressive behaviour, similar to idiopathic pulmonary fibrosis, with comparable functional decline and early mortality. Progressive pulmonar...

NAFLD progression in metabolic syndrome: a Raman spectroscopy and machine learning approach in an animal model.

The Analyst
Nonalcoholic fatty liver disease (NAFLD) is emerging as the leading cause of chronic liver disease in many regions, particularly in association with the rising prevalence of Metabolic syndrome (MetS), affecting more than 30% of the population worldwi...

SPP1 + macrophages facilitate pancreatic cancer progression via ITGB6-mediated interactions: evidence from integrated multi-omics analysis and experimental validation.

Immunologic research
Basement membranes (BMs) and tumor-associated macrophages (TAMs) are crucial stromal components in pancreatic cancer (PC), critically influencing disease progression. Bulk and single-cell RNA-seq (scRNA-seq) data were acquired from publicly available...