IEEE

An Explainable AdaBoost Framework for Early Kawasaki Disease Detection Using Bat Algorithm Based Feature Optimization

Abstract: Kawasaki Disease (KD) is a childhood vasculitis and the leading cause of acquired heart disease in children all over the world. The diagnosis of the disease is also difficult to make at an ...
IEEE

Nalla Chandana

AdaBoost,Adaptive Boosting,Body Mass Index,Decision Tree,Detection Of Insomnia,Extreme Gradient Boosting,Gradient Boosting,Health Data,Health Indicators,Imbalanced ...
Decrypt

Quantum Computers Could Boost AI by Processing Large Datasets More Efficiently

Researchers describe a method that feeds AI data into quantum computers in smaller batches instead of storing entire datasets ...

Google's new TurboQuant algorithm speeds up AI memory 8x, cutting costs by 50% or more

Within 24 hours of the release, community members began porting the algorithm to popular local AI libraries like MLX for ...
GitHub

Healthy Life Expectancy (HALE) Analysis and Prediction using Machine Learning

This project analyzes and predicts Healthy Life Expectancy at age 60 using machine learning models trained on World Health Organization (WHO) health and socio-economic data from 185 countries ...
GitHub

The Unreasonable Effectiveness of Data for Recommender Systems

This repository contains the experimental framework and thesis artifacts for a large-scale study of how recommender-system performance changes as the size of the interaction dataset increases. The ...