BACKGROUND: Mental stress-induced myocardial ischemia is often clinically silent and associated with increased cardiovascular risk, particularly in women. Conventional ECG-based detection is limited, ...

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

In this tutorial, we show how we treat prompts as first-class, versioned artifacts and apply rigorous regression testing to large language model behavior using MLflow. We design an evaluation pipeline ...

The rapid uptake of supervised machine learning (ML) in clinical prediction modelling, particularly for binary outcomes based on tabular data, has sparked debate about its comparative advantage over ...

Predicting performance for large-scale industrial systems—like Google’s Borg compute clusters—has traditionally required extensive domain-specific feature engineering and tabular data representations, ...

Background: Acute ST-segment elevation myocardial infarction (STEMI) is a cardiovascular emergency that is associated with a high risk of death. In this study, we developed explainable machine ...

In any Tkinter program, the first thing you need is a window. This window will act as a container for your app. This line brings the Tkinter library into your program. We give it the nickname tk so we ...

The Cox model is used to assess the effect of a given covariate on time-to-event outcomes in terms of HRs. For example, in a randomized clinical trial comparing a novel treatment regimen versus a ...

Abstract: In this study, we use a coarse- and fine-grained regression model and a random forest algorithm in conjunction with a data pipeline to quantify momentum in tennis matches and assess its ...