Open Heart

Artificial intelligence-based clustering to identify functional risk phenotypes in heart failure

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 ...
Scientific Research Publishing

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

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

TfELM : Extreme Learning Machines Framework with Python and TensorFlow

This framework provides a comprehensive set of tools and utilities for implementing and experimenting with Extreme Learning Machines using Python and TensorFlow. ELMs are a type of machine learning ...
GitHub

Python library for interacting with the Solvecaptcha API (captcha-solving service)

A simple and efficient method to integrate the Solvecaptcha captcha-solving service into your code, enabling the automation of solving various types of captchas. Examples of API requests for different ...
IEEE

A Comparative Analysis of Logistic Regression, Support Vector Machines, and Random Forest for Phishing Website Identification

Abstract: The effectiveness of Logistic Regression (LR), Support Vector Machines (SVM), and Random Forest (RF) in identifying phishing websites is evaluated in this study using a carefully selected ...
IEEE

Heart Disease Prediction Using Logistic Regression

Abstract: Cardiovascular diseases (CVDs) are one of the leading causes of death worldwide, and early identification is crucial to improve the patient’s prognosis. Traditional diagnostic methods for ...