Tech Xplore

New RoboReward dataset and models automate robotic training and evaluation

The advancement of artificial intelligence (AI) algorithms has opened new possibilities for the development of robots that ...

First-time use of AI for genetic circuit design demonstrated in a human cell line

There are hundreds of cell types in the human body, each with a specific role spelled out in their DNA. In theory, all it ...
Scientific Research Publishing

Boosting Algorithm: An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ()

An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ...
Frontiers

Accurate intelligent modeling of mud loss while drilling wells via soft computing methods

The final, formatted version of the article will be published soon. Accurate prediction of mud loss volume in drilling operations is a critical challenge in industries such as petroleum engineering ...
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 ...
IEEE

Salary Prediction for Employees: A Machine Learning-Based Approach

Abstract: This study aims to develop a model for predicting employee salaries using machine learning algorithms. The study uses a dataset that includes factors such as years of experience, age, gender ...
IEEE

AdaBoost-LSTM: A Hybrid Ensemble Framework for Sequential Credit Card Fraud Detection

Abstract: Credit card fraud detection is a critical task in financial systems, requiring effective algorithms to accurately classify transactions as fraudulent or non-fraudulent. This paper proposes a ...
Journal of Medical Internet Research

Detecting, Characterizing, and Mitigating Implicit and Explicit Racial Biases in Health Care Datasets With Subgroup Learnability: Algorithm Development and Validation Study

However, there have been limited substantive efforts to address bias at the level of the data used to generate algorithms in healthcare datasets. Objective: We create a simple metric (AEquity) that ...