Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Background The relationship of social determinants of health (SDOH), environmental exposures and medical history to lung function trajectories is underexplored. A better understanding of these ...

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...

Implement Logistic Regression in Python from Scratch ! In this video, we will implement Logistic Regression in Python from Scratch. We will not use any build in models, but we will understand the code ...

ABSTRACT: Heart disease remains one of the leading causes of mortality worldwide, accounting for millions of deaths annually. Early detection of individuals at risk is essential for reducing ...

Joseph Alderman et al argue that predictive models in healthcare lack adequate oversight and regulation. They highlight the potential risks to patients and call for improved governance to ensure the ...

A machine learning web application that predicts resale flat prices in Singapore using historical HDB data. Built with Scikit-learn and Streamlit, the app helps buyers and sellers estimate market ...

This set of notebooks enables the analysis of comorbidities associated with male infertility using structured EHR data. First, we identified nonoverlapping patients with male infertility and patients ...

Objective: In this study, we aim to identify the predictive variables for hemiplegic shoulder pain (HSP) through machine learning algorithms, select the optimal model and predict the occurrence of HSP ...