All Outputs (27)

Few-shot symbol detection in engineering drawings. (2024)
Journal Article
JAMIESON, L., ELYAN, E. and MORENO-GARCÍA, C.F. 2024. Few-shot symbol detection in engineering drawings. Applied artificial intelligence [online], 38(1), article number e2406712. Available from: https://doi.org/10.1080/08839514.2024.2406712

Recently, there has been significant interest in digitizing engineering drawings due to their complexity and practical benefits. Symbol digitization, a critical aspect in this field, is challenging as utilizing Deep Learning-based methods to recogniz... Read More about Few-shot symbol detection in engineering drawings..

Enhancing systematic reviews: an in-depth analysis on the impact of active learning parameter combinations for biomedical abstract screening. (2024)
Journal Article
OFORI-BOATENG, R., TRUJILLO-ESCOBAR, T.G., ACEVES-MARTINS, M., WIRATUNGA, N. and MORENO-GARCIA, C.F. 2024. Enhancing systematic reviews: an in-depth analysis on the impact of active learning parameter combinations for biomedical abstract screening. Artificial intelligence in medicine [online], 157, article number 102989. Available from: https://doi.org/10.1016/j.artmed.2024.102989

Systematic Review (SR) are foundational to influencing policies and decision-making in healthcare and beyond. SRs thoroughly synthesise primary research on a specific topic while maintaining reproducibility and transparency. However, the rigorous nat... Read More about Enhancing systematic reviews: an in-depth analysis on the impact of active learning parameter combinations for biomedical abstract screening..

Towards fully automated processing and analysis of construction diagrams: AI-powered symbol detection. (2024)
Journal Article
JAMIESON, L., MORENO-GARCIA, C.F. and ELYAN, E. [2024]. Towards fully automated processing and analysis of construction diagrams: AI-powered symbol detection. International journal on document analysis and recognition [online], Latest Articles. Available from: https://doi.org/10.1007/s10032-024-00492-9

Construction drawings are frequently stored in undigitised formats and consequently, their analysis requires substantial manual effort. This is true for many crucial tasks, including material takeoff where the purpose is to obtain a list of the equip... Read More about Towards fully automated processing and analysis of construction diagrams: AI-powered symbol detection..

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 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], 16(3), pages 1141-1160. 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..

Robust cardiac segmentation corrected with heuristics. (2023)
Journal Article
CERVANTES-GUZMÁN, A., MCPHERSON, K., OLVERES, J., MORENO-GARCÍA, C.F., ROBLES, F.T., ELYAN, E. and ESCALANTE-RAMÍREZ, B. 2023. Robust cardiac segmentation corrected with heuristics. PLoS ONE [online], 18(10), article e0293560. https://doi.org/10.1371/journal.pone.0293560

Cardiovascular diseases related to the right side of the heart, such as Pulmonary Hypertension, are some of the leading causes of death among the Mexican (and worldwide) population. To avoid invasive techniques such as catheterizing the heart, improv... Read More about Robust cardiac segmentation corrected with heuristics..

A novel application of machine learning and zero-shot classification methods for automated abstract screening in systematic reviews. (2023)
Journal Article
MORENO-GARCIA, C.F., JAYNE, C., ELYAN, E. and ACEVES-MARTINS, M. 2023. A novel application of machine learning and zero-shot classification methods for automated abstract screening in systematic reviews. Decision analytics journal [online], 6, article 100162. Available from: https://doi.org/10.1016/j.dajour.2023.100162

Zero-shot classification refers to assigning a label to a text (sentence, paragraph, whole paper) without prior training. This is possible by teaching the system how to codify a question and find its answer in the text. In many domains, especially he... Read More about A novel application of machine learning and zero-shot classification methods for automated abstract screening in systematic reviews..

Obesity and its association with mental health among Mexican children and adolescents: systematic review. (2022)
Journal Article
GODINA-FLORES, N.L., GUTIERREZ-GÓMEZ, Y.Y., GARCÍA-BOTELLO, M., LÓPEZ-CRUZ, L., MORENO-GARCÍA, C.F. and ACEVES-MARTINS, M. 2023. Obesity and its association with mental health among Mexican children and adolescents: systematic review. Nutrition reviews [online], 81(6). pages 658-669. Available from: https://doi.org/10.1093/nutrit/nuac083

Obesity and mental health issues increasingly affect children and adolescents, but whether obesity is a risk factor for mental health issues is unclear. To systematically review the association between obesity and mental health issues (ie, anxiety a... Read More about Obesity and its association with mental health among Mexican children and adolescents: systematic review..

Cultural factors related to childhood and adolescent obesity in Mexico: a systematic review of qualitative studies. (2022)
Journal Article
ACEVES-MARTINS, M., LÓPEZ-CRUZ, L., GARCÍA-BOTELLO, M., GODINA-FLORES, N.L., GUTIERREZ-GÓMEZ, Y.Y. and MORENO-GARCÍA, C.F. 2022. Cultural factors related to childhood and adolescent obesity in Mexico: a systematic review of qualitative studies. Obesity reviews [online], 23(9), article e13461. Available from: https://doi.org/10.1111/obr.13461

Culture and culturally specific beliefs or practices may influence perceptions and decisions, potentially contributing to childhood obesity. The objective of this study is to identify the cultural factors (expressed through decisions, behaviors, indi... Read More about Cultural factors related to childhood and adolescent obesity in Mexico: a systematic review of qualitative studies..

Obesity and oral health in Mexican children and adolescents: systematic review and meta-analysis. (2022)
Journal Article
ACEVES-MARTINS, M., GODINA-FLORES, N.L., GUTIERREZ-GÓMEZ, Y.Y., RICHARDS, D., LÓPEZ-CRUZ, L., GARCÍA-BOTELLO, M. and MORENO-GARCÍA, C.F. 2021. Obesity and oral health in Mexican children and adolescents: systematic review and meta-analysis. Nutrition reviews [online], 80(6), pages 1694-1710. Available from: https://doi.org/10.1093/nutrit/nuab088

Context: A relationship between obesity and poor oral health has been reported. Objective: To investigate the association between overweight/obesity and oral health in Mexican children and adolescents. Data Sources: A literature search was conducted... Read More about Obesity and oral health in Mexican children and adolescents: systematic review and meta-analysis..

Implementation of NAO robot maze navigation based on computer vision and collaborative learning. (2022)
Journal Article
MAGALLÁN-RAMÍREZ, D., MARTÍNEZ-AGUILAR, J.D., RODRÍGUEZ-TIRADO, A., BALDERAS, D., LÓPEZ-CAUDANA, E.O. AND MORENO-GARCÍA, C.F. 2022. Implementation of NAO robot maze navigation based on computer vision and collaborative learning. Frontiers in robotics and AI [online], 9, article 834021. Available from: https://doi.org/10.3389/frobt.2022.834021

Maze navigation using one or more robots has become a recurring challenge in scientific literature and real life practice, with fleets having to find faster and better ways to navigate environments such as a travel hub, airports, or for evacuation of... Read More about Implementation of NAO robot maze navigation based on computer vision and collaborative learning..

Computer vision and machine learning for medical image analysis: recent advances, challenges, and way forward. (2022)
Journal Article
ELYAN, E., VUTTIPITTAYAMONGKOL, P., JOHNSTON, P., MARTIN, K., MCPHERSON, K., MORENO-GARCIA, C.F., JAYNE, C. and SARKER, M.M.K. 2022. Computer vision and machine learning for medical image analysis: recent advances, challenges, and way forward. Artificial intelligence surgery [online], 2, pages 24-25. Available from: https://doi.org/10.20517/ais.2021.15

The recent development in the areas of deep learning and deep convolutional neural networks has significantly progressed and advanced the field of computer vision (CV) and image analysis and understanding. Complex tasks such as classifying and segmen... Read More about Computer vision and machine learning for medical image analysis: recent advances, challenges, and way forward..

Using artificial intelligence methods for systematic review in health sciences: a systematic review. (2022)
Journal Article
BLAIZOT, A., VEETTIL, S.K., SAIDOUNG, P., MORENO-GARCIA, C.F., WIRATUNGA, N., ACEVES-MARTINS, M., LAI, N.M. and CHAIYAKUNAPRUK, N. 2022. Using artificial intelligence methods for systematic review in health sciences: a systematic review. Research synthesis methods [online], 13(3), pages 353-362. Available from: https://doi.org/10.1002/jrsm.1553

The exponential increase in published articles makes a thorough and expedient review of literature increasingly challenging. This review delineated automated tools and platforms that employ artificial intelligence (AI) approaches and evaluated the re... Read More about Using artificial intelligence methods for systematic review in health sciences: a systematic review..

Interventions to prevent obesity in Mexican children and adolescents: systematic review. (2021)
Journal Article
ACEVES-MARTINS, M., LÓPEZ-CRUZ, L., GARCÍA-BOTELLO, M., GUTIERREZ-GÓMEZ, Y.Y. and MORENO-GARCÍA, C.F. 2022. Interventions to prevent obesity in Mexican children and adolescents: systematic review. Prevention science [online], 23(4), pages 563-586. Available from: https://doi.org/10.1007/s11121-021-01316-6

The prevalence of overweight and obesity has been rising among Mexican children and adolescents in the last decades. To systematically review obesity prevention interventions delivered to Mexican children and adolescents. Thirteen databases and one s... Read More about Interventions to prevent obesity in Mexican children and adolescents: systematic review..

Interventions to treat obesity in Mexican children and adolescents: systematic review and meta-analysis. (2021)
Journal Article
ACEVES-MARTINS, A., LÓPEZ-CRUZ, L., GARCÍA-BOTELLO, M., GUTIERREZ-GÓMEZ, Y.Y. and MORENO-GARCÍA, C.F. 2022. Interventions to treat obesity in Mexican children and adolescents: systematic review and meta-analysis. Nutrition reviews [online], 80(3), pages 544-560. Available from: https://doi.org/10.1093/nutrit/nuab041

Context: Prevalence of overweight and obesity has been rising in the past 3 decades among Mexican children and adolescents. Objective: To systematically review experimental studies evaluating interventions to treat obesity in Mexican children and ado... Read More about Interventions to treat obesity in Mexican children and adolescents: systematic review and meta-analysis..

Object detection, distributed cloud computing and parallelization techniques for autonomous driving systems. (2021)
Journal Article
MEDINA, E.C.G., ESPITIA, V.M.V., SILVA, D.C., DE LAS CUEVAS, S.F.R., HIRATA, M.P., CHEN, A.Z., GONZÁLEZ, J.A.G., BUSTAMANTE-BELLO, R. and MORENO-GARCÍA, C.F. 2021. Object detection, distributed cloud computing and parallelization techniques for autonomous driving systems. Applied sciences [online], 11(7), article 2925. Available from: https://doi.org/10.3390/app11072925

Autonomous vehicles are increasingly becoming a necessary trend towards building the smart cities of the future. Numerous proposals have been presented in recent years to tackle particular aspects of the working pipeline towards creating a functional... Read More about Object detection, distributed cloud computing and parallelization techniques for autonomous driving systems..

CDSMOTE: class decomposition and synthetic minority class oversampling technique for imbalanced-data classification. (2020)
Journal Article
ELYAN, E., MORENO-GARCIA, C.F. and JAYNE, C. 2021. CDSMOTE: class decomposition and synthetic minority class oversampling technique for imbalanced-data classification. Neural computing and applications [online], 33(7), pages 2839-2851. Available from: https://doi.org/10.1007/s00521-020-05130-z

Class-imbalanced datasets are common across several domains such as health, banking, security, and others. The dominance of majority class instances (negative class) often results in biased learning models, and therefore, classifying such datasets re... Read More about CDSMOTE: class decomposition and synthetic minority class oversampling technique for imbalanced-data classification..

Reducing human effort in engineering drawing validation. (2020)
Journal Article
RICA, E., MORENO-GARCÍA, C.F., ÁLVAREZ, S. and SERRATOS, F. 2020. Reducing human effort in engineering drawing validation. Computers in industry [online], 117, article ID 103198. Available from: https://doi.org/10.1016/j.compind.2020.103198

Oil & Gas facilities are extremely huge and have complex industrial structures that are documented using thousands of printed sheets. During the last years, it has been a tendency to migrate these paper sheets towards a digital environment, with the... Read More about Reducing human effort in engineering drawing validation..

Generalised median of graph correspondences. (2019)
Journal Article
MORENO-GARCÍA, C.F. and SERRATOSA, F. 2019. Generalised median of graph correspondences. Pattern recognition letters [online], 125, pages 389-395. Available from: https://doi.org/10.1016/j.patrec.2019.05.015

A graph correspondence is defined as a function that maps the elements of two attributed graphs. Due to the increasing availability of methods to perform graph matching, numerous graph correspondences can be deducted for a pair of attributed graphs.... Read More about Generalised median of graph correspondences..