Background This study aims to develop an interpretable machine learning model using SHapley Additive exPlanations (SHAP) to predict favorable outcomes based on clinical, imaging, and angiographic data ...
The Consumer Technology Association (CTA) has released a new artificial intelligence standard that requires model developers to meet specific accuracy and explainability requirements for pre-market ...
Dr. Bin Tang, Founder & CEO of Noah Digital, is an internationally recognized AI & digital marketing leader & author of “Local to Global.” For years, digital marketing has been synonymous with ...
Discover a smarter way to grow with Learn with Jay, your trusted source for mastering valuable skills and unlocking your full potential. Whether you're aiming to advance your career, build better ...
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 ...
German software company PVRadar Labs has released a Python programming toolbox for industry practitioners that are building site-specific models. The package provides a shortcut to to customize yield ...
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 ...
Predictive Modelling for Heart Disease Risk Assessment Using Logistic Regression in Machine Learning
Abstract: Worldwide, cardiovascular disease has remained one of the topmost killers among all diseases. This has stirred a high interest in prognostic models with early detection and prevention ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback