AIMC Topic: Registries

Clear Filters Showing 1 to 10 of 362 articles

Predicting the progression of difficult-to-treat rheumatoid arthritis by a machine learning scoring system, from the FIRST registry.

RMD open
OBJECTIVES: This study aimed to develop and validate a prediction model for the future progression of difficult-to-treat rheumatoid arthritis (D2T RA) and support the precise use of biologic and targeted synthetic disease-modifying antirheumatic drug...

Development and external validation of machine learning approaches for risk prediction of cardiovascular disease in individuals with schizophrenia: a nationwide Swedish and Danish study.

BMJ mental health
BACKGROUND: Currently available cardiovascular disease (CVD) risk prediction tools may underestimate the risk in individuals with schizophrenia. OBJECTIVE: To develop and externally validate 5-year CVD risk prediction models for people with schizophr...

Predicting symptomatic intracranial hemorrhage after endovascular treatment of vertebrobasilar artery occlusion: PEACE score.

Journal of neurointerventional surgery
BACKGROUND: Current clinical decision tools for assessing the risk of symptomatic intracranial hemorrhage (sICH) in patients with vertebrobasilar artery occlusion (VBAO) who received endovascular treatment (EVT) have limited performance. This study d...

Development and Validation of an Interpretable Hemodynamics-Based Machine Learning Model for Predicting Cerebral Arteriovenous Malformation Rupture.

Translational stroke research
Cerebral arteriovenous malformation (AVM) is a cerebrovascular disease associated with a risk of intracranial hemorrhage. Currently, most risk prediction models for AVM rupture are based on demographic characteristics and lesion morphology, while qua...

Comparison of Machine Learning Models for Colon Cancer Survival: Predictive Modeling Approach.

JMIR cancer
BACKGROUND: Colon cancer is a leading cause of cancer-related deaths worldwide, with survival influenced by risk factors, treatment type, and patient characteristics. Traditional statistical models, such as Kaplan-Meier curves, have been widely used ...

Towards an AI-driven registry for postoperative complications: a proof-of-concept study evaluating the opportunities and challenges of AI models.

BMJ health & care informatics
OBJECTIVES: Postoperative complications (PCs) require substantial resources to manage and are cumbersome to monitor. Artificial intelligence (AI), particularly natural language processing (NLP), offers a potential solution by automating and streamlin...

Worse survival despite indolent features for triple-negative invasive lobular carcinoma: a Swedish nationwide registry-based study.

Breast cancer research and treatment
PURPOSE: To evaluate differences in clinical outcomes, treatments received, recurrence, and sociodemographic characteristics in patients with triple-negative breast cancer (TNBC) classified as invasive lobular carcinoma (TNBC-ILC) or invasive carcino...

Introducing FREM: a decision-support approach for automated identification of individuals at high imminent fracture risk.

Archives of osteoporosis
UNLABELLED: This study used explainable AI to improve the Danish FREM model for predicting one-year risk of major osteoporotic fractures in over 2.4 million individuals aged ≥ 45. A DART boosting algorithm improved performance (AUC 0.77), with explai...

Incidence and severity of aortic stenosis according to machine learning predicted risk of atrial fibrillation.

Scientific reports
Atrial fibrillation (AF) and aortic stenosis (AS) are two common progressive conditions affecting older persons that share pathobiological pathways. Early detection of AS is critical for improving outcomes, but no prediction tool exists to inform dec...

Machine learning-assisted screening of clinical features for predicting difficult-to-treat rheumatoid arthritis.

Scientific reports
To identify clinical features that predict the risk of meeting difficult-to-treat (D2T) rheumatoid arthritis (RA) definition in advance. This retrospective analysis included RA patients from the ATTRA registry who initiated biologic (b-) or targeted ...