Outputs (4)

Towards the automation of systematic reviews using natural language processing, machine learning, and deep learning: a comprehensive review. (2024)
Journal Article
OFORI-BOATENG, R., ACEVES-MARTINS, M., WIRATUNGA, N. and MORENO-GARCIA, C.F. 2024. Towards the automation of systematic reviews using natural language processing, machine learning, and deep learning: a comprehensive review. Artificial intelligence review [online], 57(8), article number 200. Available from: https://doi.org/10.1007/s10462-024-10844-w

Systematic reviews (SRs) constitute a critical foundation for evidence-based decision-making and policy formulation across various disciplines, particularly in healthcare and beyond. However, the inherently rigorous and structured nature of the SR pr... Read More about Towards the automation of systematic reviews using natural language processing, machine learning, and deep learning: a comprehensive review..

A zero-shot monolingual dual stage information retrieval system for Spanish biomedical systematic literature reviews. (2024)
Conference Proceeding
OFORI-BOATENG, R., ACEVES-MARTINS, M., WIRATUNGA, N. and MORENO-GARCIA, C. 2024. A zero-shot monolingual dual stage information retrieval system for Spanish biomedical systematic literature reviews. In Duh, K., Gomez, H. and Bethard, S. (eds.) Proceedings of the 2024 North American Chapter of the Association for Computational Linguistics conference (NAACL 2024): human language technologies, 16-21 June 2024, Mexico City, Mexico. Stroudsburg, PA: ACL [online], volume 1: long papers, pages 3725-3736. Available from: https://aclanthology.org/2024.naacl-long.206

Systematic Reviews (SRs) are foundational in healthcare for synthesising evidence to inform clinical practices. Traditionally skewed towards English-language databases, SRs often exclude significant research in other languages, leading to potential b... Read More about A zero-shot monolingual dual stage information retrieval system for Spanish biomedical systematic literature reviews..

A review of deep learning methods for digitisation of complex documents and engineering diagrams. (2024)
Journal Article
JAMIESON, L., MORENO-GARCIA, C.F. and ELYAN, E. 2024. A review of deep learning methods for digitisation of complex documents and engineering diagrams. Artificial intelligence review [online], 57(6), article number 136. Available from: https://doi.org/10.1007/s10462-024-10779-2

This paper presents a review of deep learning on engineering drawings and diagrams. These are typically complex diagrams, that contain a large number of different shapes, such as text annotations, symbols, and connectivity information (largely lines)... Read More about A review of deep learning methods for digitisation of complex documents and engineering diagrams..

Two-layer ensemble of deep learning models for medical image segmentation. (2024)
Journal Article
DANG, T., NGUYEN, T.T., MCCALL, J., ELYAN, E. and MORENO-GARCÍA, C.F. 2024. Two-layer ensemble of deep learning models for medical image segmentation. Cognitive computation [online], In Press. Available from: https://doi.org/10.1007/s12559-024-10257-5

One of the most important areas in medical image analysis is segmentation, in which raw image data is partitioned into structured and meaningful regions to gain further insights. By using Deep Neural Networks (DNN), AI-based automated segmentation al... Read More about Two-layer ensemble of deep learning models for medical image segmentation..