The Faculty of Engineering at Universidad Panamericana, Mexico City campus, consolidates its leadership in cutting-edge research with the publication of the book Machine Learning Methods in Biomedical Field: Computer-Aided Diagnostics, Healthcare and Biology Applications.
The book, published in Springer’s Studies in Computational Intelligence series, was edited by three distinguished academics from the Faculty of Engineering: Dr. Ernesto Moya Albor, Dr. Hiram Eredín Ponce Espinosa, and Dr. Jorge Eduardo Brieva Rico.
In addition, the volume includes editorial contributions from Dr. Sandra L. Gómez-Coronel of the Instituto Politécnico Nacional and Dr. Diego Renza Torres of the Universidad Militar Nueva Granada in Bogotá, Colombia.
According to Dr. Ernesto Moya, the initiative responds to a clear objective:
“To publish a book every one or two years in collaboration with researchers from the Faculty of Engineering itself, as well as from other faculties and schools of Universidad Panamericana and from national and international research centers.”
This volume is, in fact, the third book they have published as editors since 2020.
A Convergence of Knowledge to Address Biomedical Challenges
The book brings together research that applies computational intelligence and machine learning to problems in the biomedical field, demonstrating how these technologies can improve computer-aided medical diagnostic systems, healthcare tools, and biological applications.
“This book brings together a multidisciplinary collection of innovative machine learning approaches applied to the biomedical field,” Dr. Moya emphasized. “Its objective is to show how artificial intelligence–based technologies can drive the development of new computer-aided diagnostic systems, healthcare tools, and biological applications,” he added.
Among the topics addressed are fuzzy systems, artificial neural networks, evolutionary computation, Bayesian networks, learning theory, and machine learning, reflecting the breadth and depth of the research lines promoted by Universidad Panamericana.
From the Laboratory to Society: Tangible Impact on Health
Beyond its theoretical value, the book stands out for its potential application in solving real-world problems. The findings and methods it contains are aimed at integration into computer-aided medical diagnostic systems, healthcare support tools, and intelligent platforms for biological analysis.
“These technologies contribute to improving diagnostic accuracy, optimizing clinical processes, and accelerating the development of personalized solutions for patients,” the researcher stated.
He further noted:
“Taken together, the contributions of the book demonstrate how advances in the field of computational intelligence can be translated into tangible benefits for society.”
A Collaborative and Rigorous Effort
The project is the result of international collaboration among researchers from diverse disciplines and universities. All contributions were peer-reviewed, ensuring the scientific quality of the volume.
The publication is primarily aimed at graduate students, researchers, and professionals in computer science, computer engineering, and biomedical engineering. However, it is also highly relevant for graduate students in information technologies, mechatronics, medicine, biology, and for anyone interested in the intersection between technology and health.
Laying the Foundations for the Future of Research at UP
For the editors, the completion of this project is a source of great pride and satisfaction.
“I feel very proud to have led this project and to have been closely involved in the entire editorial process, collaborating with faculty editors and authors, as well as with national and international researchers,” shared Dr. Moya Albor.
One aspect that Dr. Moya highlighted with particular satisfaction was the opportunity to publish in Springer’s Studies in Computational Intelligence series and to work with Dr. Thomas Ditzinger, Editorial Director of Interdisciplinary Applied Sciences at Springer, which reflects the high academic level of the work.
Finally, the academic noted that this book lays the groundwork for future research lines within the Faculty of Engineering at Universidad Panamericana:
“The project aims to disseminate the knowledge generated within the faculty while simultaneously strengthening internal and external academic collaboration. It also seeks to promote interdisciplinary work across diverse areas of knowledge.”
With this publication, Universidad Panamericana reaffirms its commitment to technological innovation, scientific training, and knowledge transfer, positioning itself as a national and international reference in the field of computational intelligence applied to biomedicine.
Find Machine Learning Methods in Biomedical Field: Computer-Aided Diagnostics, Healthcare and Biology Applications at:
https://link.springer.com/book/10.1007/978-3-031-96328-5
https://www.amazon.com.mx/Machine-Learning-Methods-Biomedical-Field-ebook/dp/B0FVQCNFY6
Bibliographic Reference
Moya-Albor, E., Ponce, H., Brieva, J., Gómez-Coronel, S. L., & Torres Renza, D. (Eds.). (2026). Machine Learning Methods in Biomedical Field: Computer-Aided Diagnostics, Healthcare and Biology Applications. Springer, Cham. https://doi.org/10.1007/978-3-031-96328-5
