AI vs Machine Learning: What is the Difference?

AI (Artificial Intelligence) is a broad concept and its goal is to create intelligent systems whereas Machine Learning is a ...
EurekAlert!

New method improves the reliability of statistical estimations

MIT researchers developed a method that generates more accurate uncertainty measures for certain types of estimation. This could help improve the reliability of data analyses in areas like economics, ...
Beebom

What is Deep Learning in AI? Understanding How AI Really Works

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter ...
EurekAlert!

Rohan Chand Sahu from Indian Institute of Technology (IIT) explores AI-powered nanomedicine: Machine learning redefines precision cancer drug delivery

This review systematically examines the integration of machine learning (ML) and artificial intelligence (AI) in nanomedicine ...
The Lancet

Effective sample size for individual risk predictions: quantifying uncertainty in machine learning models

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...
Frontiers

Efficient tree species classification using machine and deep learning algorithms based on UAV-LiDAR data in North China

Introduction: The unmanned aerial vehicle -based light detection and ranging (UAV-LiDAR) can quickly acquire the three-dimensional information of large areas of vegetation, and has been widely used in ...
Scientific Research Publishing

Lindebaum, D., Vesa, M., & den Hond, F. (2020). Insights from “the Machine Stops” to Better Understand Rational Assumptions in Algorithmic Decision Making and Its ...

ABSTRACT: This study aims to investigate the effects of FinTech disruption on systemic risk and economic stability of emerging economies including Pakistan, Nepal and Bangladesh. In the context of the ...
BMJ

Machine learning approaches to injury risk prediction in sport: a scoping review with evidence synthesis

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...
eWeek

Types of AI Models: A Deep Dive into AI Architecture

Dr. Chris Hillman, Global AI Lead at Teradata, joins eSpeaks to explore why open data ecosystems are becoming essential for enterprise AI success. In this episode, he breaks down how openness — in ...