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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..

Zero-error digitisation and contextualisation of piping and instrumentation diagrams using node classification and sub-graph search. (2022)
Conference Proceeding
RICA, E., ALVAREZ, S., MORENO-GARCIA, C.F. and SERRATOSA, F. 2022. Zero-error digitisation and contextualisation of piping and instrumentation diagrams using node classification and sub-graph search. In Krzyzak, A., Suen, C.Y., Torsello, A. and Nobile, N. (eds.) Structural, syntactic, and statistical pattern recognition: proceedings of the 2022 Joint International Association for Pattern Recognition (IAPR) international workshops on statistical techniques in pattern recognition, and structural and syntactic pattern recognition (S+SSPR 2022), 26-27 August 2022, Montréal, Canada. Lecture notes in computer science, 13813. Cham: Springer [online], pages 274-282. Available from: https://doi.org/10.1007/978-3-031-23028-8_28

Thousands of huge printed sheets depicting engineering drawings keep record of complex industrial structures from Oil & Gas facilities. Currently, there is a trend of digitising these drawings, having as final end the regeneration of the original com... Read More about Zero-error digitisation and contextualisation of piping and instrumentation diagrams using node classification and sub-graph search..

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. 2022. Obesity and its association with mental health among Mexican children and adolescents: systematic review. Nutrition reviews [online], Advanced Articles. 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..

Cross domain evaluation of text detection models. (2022)
Conference Proceeding
ALI-GOMBE, A., ELYAN, E., MORENO-GARCÍA, C. and JAYNE, C. 2022. Cross domain evaluation of text detection models. In Pimenidis, E., Angelov, P., Jayne, C., Papaleonidas, A. and Aydin, M. (eds.) Artificial neural networks and machine learning - ICANN 2022: proceedings of the 31st International conference on artificial neural networks (ICANN 2022), 6-9 September 2022, Bristol, UK, part III. Lecture notes in computer science, 13531. Cham: Springer [online], pages 50-61. Available from: https://doi.org/10.1007/978-3-031-15934-3_5

Text detection is a very common task across a wide range of domains, such as document image analysis, remote identity verification, amongst others. It is also considered an integral component of any text recognition system, where the performance of r... Read More about Cross domain evaluation of text detection models..

TransSLC: skin lesion classification in dermatoscopic images using transformers. (2022)
Conference Proceeding
SARKER, M.M.K., MORENO-GARCÍA, C.F., REN, J. and ELYAN, E. 2022. TransSLC: skin lesion classification in dermatoscopic images using transformers. In Yang, G., Aviles-Rivero, A., Roberts, M. and Schönlieb, C.-B. (eds.) Medical image understanding and analysis: proceedings of 26th Medical image understanding and analysis 2022 (MIUA 2022), 27-29 July 2022, Cambridge, UK. Lecture notes in computer sciences, 13413. Cham: Springer [online], pages 651-660. Available from: https://doi.org/10.1007/978-3-031-12053-4_48

Early diagnosis and treatment of skin cancer can reduce patients' fatality rates significantly. In the area of computer-aided diagnosis (CAD), the Convolutional Neural Network (CNN) has been widely used for image classification, segmentation, and rec... Read More about TransSLC: skin lesion classification in dermatoscopic images using transformers..

A general framework for partial to full image registration. (2022)
Working Paper
MORENO-GARCÍA, C.F. and SERRATOSA, F. 2022. A general framework for partial to full image registration. arXiv [online]. Available from: https://doi.org/10.48550/arXiv.2207.06387

Image registration is a research field in which images must be compared and aligned independently of the point of view or camera characteristics. In some applications (such as forensic biometrics, satellite photography or outdoor scene identification... Read More about A general framework for partial to full image registration..

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. [Appendices] (2022)
Dataset
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. [Appendices]. Research synthesis methods [online], 1393), pages 353-362. Available from: https://onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002%2Fjrsm.1553&file=jrsm1553-sup-0001-supinfo.docx

Systematic reviews are fundamental to evidence-based decision making, as they use a comprehensive search and synthesis of the available literature. Such an operation usually requires a team of reviewers to evaluate thousands of articles. With the exp... Read More about Using artificial intelligence methods for systematic review in health sciences: a systematic review. [Appendices].

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..

A deep learning digitisation framework to mark up corrosion circuits in piping and instrumentation diagrams. (2021)
Conference Proceeding
TORAL, L., MORENO-GARCIA, C.F., ELYAN, E. and MEMON, S. 2021. A deep learning digitisation framework to mark up corrosion circuits in piping and instrumentation diagrams. In Barney Smith, E.H. and Pal, U. (eds.) Document analysis and recognition: ICDAR 2021 workshops, part II: proceedings of 16th International conference on document analysis and recognition 2021 (ICDAR 2021), 5-10 September 2021, Lausanne, Switzerland. Lecture notes in computer science, 12917. Cham: Springer [online], pages 268-276. Available from: https://doi.org/10.1007/978-3-030-86159-9_18

Corrosion circuit mark up in engineering drawings is one of the most crucial tasks performed by engineers. This process is currently done manually, which can result in errors and misinterpretations depending on the person assigned for the task. In th... Read More about A deep learning digitisation framework to mark up corrosion circuits in piping and instrumentation diagrams..

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..

Class-decomposition and augmentation for imbalanced data sentiment analysis. (2021)
Conference Proceeding
MORENO-GARCIA, C.F., JAYNE, C. and ELYAN, E. 2021. Class-decomposition and augmentation for imbalanced data sentiment analysis. In Proceedings of 2021 International joint conference on neural networks (IJCNN 2021), 18-22 July 2021, [virtual conference]. Piscataway: IEEE [online], article 9533603. Available from: https://doi.org/10.1109/IJCNN52387.2021.9533603

Significant progress has been made in the area of text classification and natural language processing. However, like many other datasets from across different domains, text-based datasets may suffer from class-imbalance. This problem leads to model's... Read More about Class-decomposition and augmentation for imbalanced data sentiment analysis..

Weighted ensemble of deep learning models based on comprehensive learning particle swarm optimization for medical image segmentation. (2021)
Conference Proceeding
DANG, T., NGUYEN, T.T., MORENO-GARCIA, C.F., ELYAN, E. and MCCALL, J. 2021. Weighted ensemble of deep learning models based on comprehensive learning particle swarm optimization for medical image segmentation. In Proceeding of 2021 IEEE (Institute of electrical and electronics engineers) Congress on evolutionary computation (CEC 2021), 28 June - 1 July 2021, Kraków, Poland : [virtual conference]. Piscataway: IEEE [online], pages 744-751. Available from: https://doi.org/10.1109/CEC45853.2021.9504929

In recent years, deep learning has rapidly become a method of choice for segmentation of medical images. Deep neural architectures such as UNet and FPN have achieved high performances on many medical datasets. However, medical image analysis algorith... Read More about Weighted ensemble of deep learning models based on comprehensive learning particle swarm optimization for medical image segmentation..

Face detection with YOLO on edge. (2021)
Conference Proceeding
ALI-GOMBE, A., ELYAN, E., MORENO-GARCIA, C.F. and ZWIEGELAAR, J. 2021. Face detection with YOLO on edge. In Iliadis, L., Macintyre, J., Jayne, C. and Pimenidis, E. (eds.). Proceedings of the 22nd Enginering applications of neural networks conference (EANN2021), 25-27 June 2021, Halkidiki, Greece. Proceedings of the International Neural Networks Society (INNS), 3. Cham: Springer [online], pages 284-292. Available from: https://doi.org/10.1007/978-3-030-80568-5_24

Significant progress has been achieved in objects detection applications such as Face Detection. This mainly due to the latest development in deep learning-based approaches and especially in the computer vision domain. However, deploying deep-learnin... Read More about Face detection with YOLO on edge..

Image pre-processing and segmentation for real-time subsea corrosion inspection. (2021)
Conference Proceeding
PIRIE, C. and MORENO-GARCIA, C.F. 2021. Image pre-processing and segmentation for real-time subsea corrosion inspection. In Iliadis, L., Macintyre, J., Jayne, C. and Pimenidis, E. (eds.). Proceedings of the 22nd Engineering applications of neural networks conference (EANN2021), 25-27 June 2021, Halkidiki, Greece. Proceedings of the International Neural Networks Society (INNS), 3. Cham: Springer [online], pages 220-231. Available from: https://doi.org/10.1007/978-3-030-80568-5_19

Inspection engineering is a highly important field in the Oil & Gas sector for analysing the health of offshore assets. Corrosion, a naturally occurring phenomenon, arises as a result of a chemical reaction between a metal and its environment, causin... Read More about Image pre-processing and segmentation for real-time subsea corrosion inspection..

Two layer ensemble of deep learning models for medical image segmentation. (2021)
Working Paper
DANG, T., NGUYEN, T.T., MCCALL, J., ELYAN, E. and MORENO-GARCÍA, C.F. 2021. Two layer ensemble of deep learning models for medical image segmentation. arXiv [online]. Available from: https://doi.org/10.48550/arXiv.2104.04809

In recent years, deep learning has rapidly become a method of choice for the segmentation of medical images. Deep Neural Network (DNN) architectures such as UNet have achieved state-of-the-art results on many medical datasets. To further improve the... Read More about Two layer ensemble of deep learning models for medical image segmentation..