Predictive modelling of metabolic syndrome in Ghanaian diabetic patients: an ensemble machine learning approach.

Objectives: The burgeoning prevalence of cardiometabolic disorders, including type 2 diabetes mellitus (T2DM) and metabolic syndrome (MetS) within Africa is concerning. Machine learning (ML) techniques offer a unique opportunity to leverage data-driven insights and construct predictive models for MetS risk, thereby enhancing the implementation of personalised prevention strategies. In this work, we employed ML techniques to develop predictive models for pre-MetS and MetS among diabetic patients.

Comparing paediatric optometric vision care in Canada over a 14-year period.

Purpose: In Canada, teaching in paediatric eye care has increased in the past decade both within the optometry curriculum and as continuing education to optometrists. Paediatric vision care guidelines have also been established by North American optometric associations. This study examined whether this exposure was associated with changes in paediatric eye care in Canada over a 14-year period.

Conceptualised psycho-medical footprint for health status outcomes and the potential impacts for early detection and prevention of chronic diseases in the context of 3P medicine.

Background: The Suboptimal Health Status Questionnaire-25 (SHSQ-25) is a distinctive medical psychometric diagnostic tool designed for the early detection of chronic diseases. However, the synaptic connections between the 25 symptomatic items and their relevance in supporting the monitoring of suboptimal health outcomes, which are precursors for chronic diseases, have not been thoroughly evaluated within the framework of predictive, preventive, and personalised medicine (PPPM/3PM). This baseline study explores the internal structure of the SHSQ-25 and demonstrates its discriminatory power to predict optimal and suboptimal health status (SHS) and develop photogenic representations of their distinct relationship patterns.

Validation of the Waterloo Differential Visual Acuity Test (WatDAT) and Comparison With Existing Pediatric Tests of Visual Acuity.

Purpose: The new Waterloo Differential Acuity Test (WatDAT) is designed to allow recognition visual acuity (VA) measurement in children before they can typically undertake matching tests. The study purpose was to validate WatDAT in adults with normal and reduced VA.

Methods: Eighty adults (18 to <40 years of age) participated (32 normal VA, 12 reduced VA, and 36 simulated reduced VA).