Research Topic · Peer-Reviewed

Machine Learning

Machine learning is the branch of artificial intelligence concerned with algorithms that infer patterns from data and improve their predictive performance with experience, rather than following rules an engineer has written out by hand. A model is trained on examples, learns a mapping from inputs to outputs, and is …

Curated from this journal's research 📚 9 peer-reviewed articles cited Cited 50× across the literature 🗓 Reviewed July 2026

Overview

Machine learning is the branch of artificial intelligence concerned with algorithms that infer patterns from data and improve their predictive performance with experience, rather than following rules an engineer has written out by hand. A model is trained on examples, learns a mapping from inputs to outputs, and is then evaluated on data it has not seen. Methods are commonly grouped into supervised learning, in which labelled examples teach the model to predict a known target; unsupervised learning, which finds structure such as clusters or latent factors in unlabelled data; and reinforcement learning, in which an agent learns from feedback signals. Core algorithm families include linear and logistic regression, decision trees and tree ensembles, support vector machines, time-series models, and deep neural networks. Across the work collected here, machine learning is applied to disease prediction from clinical and epidemiological datasets, image-based detection of plant disease and weeds through transfer learning and deep networks, forecasting of pandemic case counts, and tumour grading. Recurring concerns are feature selection, model interpretability, generalisation beyond the training sample, class imbalance, and the equity and ethical questions raised when predictive systems inform decisions affecting people. These themes connect machine learning to broader debates in data science and applied analytics.

Research published in this journal

9 peer-reviewed articles, ranked by relevance. Each links to its DOI.

How this research is being cited

The 9 articles above have been cited 50 times in the scholarly literature. Citation data via OpenAlex and Crossref, updated Jun 2026.

A sample of recent works citing this journal's research on Machine Learning, linking to each citing work.

Editorial oversight

Curated from peer-reviewed research published in Applied Robotics and Artificial Intelligence.

Journal editorial board
Simon X. Yang · Canada Pasi Luukka · Finland Basil Mohammed Al-Hadithi · Spain

This page summarises published research for orientation; it is not medical or professional advice.