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...
As artificial intelligence (AI) systems become increasingly integrated into decision-making across various sectors, understanding public trust in these systems is more crucial than ever. This study presents a quantitative analysis of survey data from...
BACKGROUND: We aim to assess the diagnosis performance of an ensemble machine learning (ML) based radiomic analysis of multiparametric cardiac magnetic resonance (CMR) to differentiate light chain cardiac amyloidosis (AL-CA) and hypertrophic cardiomy...
OBJECTIVES: This study aimed to develop and validate a CT radiomics-based explainable machine learning model for precise diagnosing of malignancy and benignity specifically in endometrial cancer (EC) patients.
BACKGROUND: Gout is the most common inflammatory arthritis. Recurrent flares are common among hospitalised patients and contribute to substantial clinical and economic burden. However, the accurate prediction of inpatient recurrence remains challengi...
A cerebral aneurysm may present irregularities associated with rupture risks. However, conventional morphological parameters are limited in evaluating the aneurysm irregularity. Although the mass moment of inertia has been devised for the irregularit...
We aimed to identify and validate key predictive factors influencing 28-day survival rates in patients with diabetes and sepsis and to develop a predictive model based on these factors to assist clinical decision-making. In this retrospective cohort ...
The histological FNCLCC grade is the primary prognostic factor in soft-tissue sarcoma (STS) but fails to fully capture high risk patients. This study aimed to develop and validate a deep learning (DL) model to predict metastatic relapse-free survival...
This study aimed to develop and validate an interpretable radiomics-based machine learning model using contrast-enhanced T1-weighted imaging (CE-T1WI) to differentiate glioblastoma (GB) from primary central nervous system lymphoma (PCNSL), while comp...
OBJECTIVE: To investigate the interplay between the genetic predisposition to successful ageing and air pollution on lung disease in healthy aged German women under the hypothesis that ageing and lung diseases share mechanisms of oxidative stress and...
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