Research Topic · Peer-Reviewed

Deep Learning

Deep learning is a subfield of machine learning that uses artificial neural networks with many layers to learn hierarchical representations directly from data. By stacking layers of interconnected units, deep networks progressively transform raw inputs into increasingly abstract features, enabling them to model comp…

Curated from this journal's research 📚 9 peer-reviewed articles cited Cited 28× across the literature 🔖 ISSN 2641-5526 🗓 Reviewed July 2026

Overview

Deep learning is a subfield of machine learning that uses artificial neural networks with many layers to learn hierarchical representations directly from data. By stacking layers of interconnected units, deep networks progressively transform raw inputs into increasingly abstract features, enabling them to model complex, non-linear relationships without hand-engineered feature extraction. Training relies on large datasets and on optimisation by backpropagation and gradient descent, adjusting the weights of the network to minimise prediction error. Distinct architectures suit different problems: convolutional neural networks for images, recurrent and sequence models for time series and language, and transfer learning, in which a model pretrained on one task is adapted to a related task with limited data. Deep learning underpins advances in computer vision, natural language processing, speech recognition, and decision support, and is increasingly applied in medicine, agriculture, and the analysis of complex datasets. The articles collected here, drawn from work on medical informatics and decision-making, examine deep learning and transfer learning for detecting plant leaf diseases and weeds, time-series and Bayesian modelling for prediction, and the role of artificial intelligence in healthcare. Recurring themes include neural-network architectures, transfer learning, image classification and prediction, model generalisation, and the integration of deep learning into applied decision-making. The topic sits within artificial intelligence, data science, and informatics.

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 28 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 Deep Learning, linking to each citing work.

Editorial oversight

Curated from peer-reviewed research published in Medical Informatics and Decision Making (ISSN 2641-5526).

Journal editorial board
Jennifer Fink · united states Lifeng Peng · New Zealand Prasad Konkalmatt · United States

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