Open Heart

Machine learning-based cardiovascular risk calculator for non-cardiac surgery

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

Development and evaluation of a diagnostic aiding tool for differentiating tropical fevers using artificial intelligence approach: a study protocol from tertiary care hospital ...

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 ...
Hosted on MSN

Python neural network for multiclass classification using softmax

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...
Frontiers

Posterior averaging with Gaussian naive Bayes and the R package RandomGaussianNB for big-data classification

Department of Mathematics and Statistics, Faculty of Science and Technology, Thammasat University, Khlong Luang, Pathum Thani, Thailand RandomGaussianNB is an open-source R package implementing the ...
Hosted on MSN

Sleep Stage Classification with Python: EEG, Scikit-Learn & MNE

Explore the first part of our series on sleep stage classification using Python, EEG data, and powerful libraries like Sklearn and MNE. Perfect for data scientists and neuroscience enthusiasts!
Scientific Research Publishing

Comparative Analysis of Neural Networks and Naive Bayes for Multilingual Text Identification ()

1 Department of Computer Science, Rochester Institute of Technology, Rochester, USA. 2 Department of Computer Science, Rutgers University, New Brunswick, USA. Language identification is a fundamental ...
Frontiers

What goes on when the lights go off? Using machine learning techniques to characterize a child’s settling down period

Objectives: Current approaches to objective measurement of sleep disturbances in children overlook the period prior to sleep, or the settling down time. Using machine learning techniques, we ...
Visual Studio Magazine

Naive Bayes Regression Using C#

The goal of a machine learning regression problem is to predict a single numeric value. There are roughly a dozen different regression techniques such as basic linear regression, k-nearest neighbors ...
IEEE

High-Confidence Classification of Partial Discharge Acoustic Signals Using Bayesian Networks for Uncertainty Quantification

Abstract: Acoustic emission (AE) detection is a nonintrusive technique for monitoring transformer conditions by capturing emissions from partial discharges (PDs), hotspots, and noise. Machine learning ...