AI & Society, states that algorithmic systems often construct competing but equally valid “model-worlds,” offering empirical support for a philosophical claim that evidence alone cannot uniquely ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...

Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...

Background Approximately one in three patients with acute ischemic stroke (AIS) suffer from a premorbid disability prior to ...

Primary and secondary outcome measures Children’s mental health was assessed using the Mental Health Test; parental anxiety and depression were measured with the Generalised Anx ...

Objectives This study aimed to determine whether certain lifestyle factors, specifically alcohol consumption, smoking, physical activity, sleep duration and sleep quality, are associated with an ...

Background As the threat of child malnutrition increases, the focus remains mostly on short-term consequences. Long-term ...

Introduction The Netherlands implemented a supermarket tobacco sales ban on 1 July 2024. This study aimed to evaluate supermarkets’ compliance with the ban and potential unintended impacts on tobacco ...

Linear regression is the most fundamental machine learning technique to create a model that predicts a single numeric value. One of the three most common techniques to train a linear regression model ...