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Development and validation of an interpretable machine learning model for predicting Philadelphia chromosome-positive acute lymphoblastic leukaemia using clinical and laboratory parameters: a single-centre retrospective study.
BMJ open
Jun 27, 2025
OBJECTIVE: To develop and validate a prediction model of Philadelphia chromosome-positive acute lymphoblastic leukaemia (Ph+ALL).
A Responsible Framework for Assessing, Selecting, and Explaining Machine Learning Models in Cardiovascular Disease Outcomes Among People With Type 2 Diabetes: Methodology and Validation Study.
JMIR medical informatics
Jun 27, 2025
BACKGROUND: Building machine learning models that are interpretable, explainable, and fair is critical for their trustworthiness in clinical practice. Interpretability, which refers to how easily a human can comprehend the mechanism by which a model ...
Using Artificial Intelligence to assess the impact of social, physical, and financial health and personality on subjective well-being in a representative, multinational sample of older European and Israeli adults.
Journal of global health
Jun 27, 2025
BACKGROUND: Subjective well-being (SWB) is an important outcome influenced by other aspects of health and personality. However, we know little about the independent effects of multiple health and personality dimensions on SWB in large, representative...
Urgency vs triage prioritisation: appropriateness of referrer-rated urgency of referrals to a public dermatology service.
The New Zealand medical journal
Jun 27, 2025
AIM: To characterise the appropriateness of community referrer-rated urgency among dermatology referrals.
Machine learning-based comparison of transperineal vs. transrectal biopsy for prostate cancer diagnosis: evaluating procedural effectiveness.
The Canadian journal of urology
Jun 27, 2025
BACKGROUND: Transrectal (TR) and transperineal (TP) biopsies are commonly used methods for diagnosing prostate cancer. However, their comparative effectiveness in conjunction with machine learning (ML) techniques remains underexplored. This study aim...
Developing interpretable machine learning models to predict length of stay and disposition decision for adult patients in emergency departments.
BMJ health & care informatics
Jun 26, 2025
OBJECTIVE: Machine learning (ML) models have emerged as tools to predict length of stay (LOS) and disposition decision (DD) in emergency departments (EDs) to combat overcrowding. However, site-specific ML models are not transferable to different site...
From laser-on time to lithotripsy duration: improving the prediction of lithotripsy duration with 'Kidney Stone Calculator' using artificial intelligence.
World journal of urology
Jun 26, 2025
INTRODUCTION: "Kidney Stone Calculator" (KSC) helps to plan flexible ureteroscopy, providing the stone volume (SV) and an estimated duration of laser lithotripsy (eLD). eLD is calculated from in vitro ablation rates and SV. KSC's accuracy has been de...
Epicardial adipose tissue, myocardial remodelling and adverse outcomes in asymptomatic aortic stenosis: a post hoc analysis of a randomised controlled trial.
Heart (British Cardiac Society)
Jun 26, 2025
BACKGROUND: Epicardial adipose tissue represents a metabolically active visceral fat depot that is in direct contact with the left ventricular myocardium. While it is associated with coronary artery disease, little is known regarding its role in aort...
Effect of the exposure to brominated flame retardants on hyperuricemia using interpretable machine learning algorithms based on the SHAP methodology.
PloS one
Jun 26, 2025
BACKGROUND: Brominated flame retardants (BFRs) are classified as important endocrine disruptors and persistent organic pollutants; nevertheless, there is no comprehensive investigation to evaluate the association between BFRs and hyperuricemia, and t...
Evaluating real-world performance of an automated offline glaucoma AI on a smartphone fundus camera across glaucoma severity stages.
PloS one
Jun 26, 2025
PURPOSE: Leveraging an artificial intelligence system (AI) for glaucoma screening can mitigate the current challenges and provide prompt detection and management crucial in averting irreversible blindness. The study reports the real-world performance...
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