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Generative AI and the scientific landscape: a bibliometric exploration of its global impact
(Editorial Académica Dragón Azteca, 2026-02-16)
Cossio Franco, Edgar Gonzalo
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Sossa Azuela, Juan Humberto
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Larios Rosillo, Víctor Manuel
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Maciel Arellano, Rocio
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Arreola Marín, María Esmeralda
The present comparative bibliometric study (2020-2025) of the Scopus and WoS databases on Generative Artificial Intelligence (GenAI) reveals accelerated growth, concentrating more than 95% of the production and reaching its peak impact in 2025. Thematically, the intersection of communication and technology/education dominates. Geographically, the United States leads production, but Asia-Pacific institutions (Hong Kong) are key. The field of GenAI is a massive trend driven by concentrated collaboration between North America and Asia.
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MICAI and the Making of AI in Mexico Through 25 Years of Data-Driven Insight
(Springer Nature Switzerland, 2025)
Avalos-Gauna, Edgar
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Palafox Novack, Leon Felipe
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Martinez-Villaseñor, Lourdes
This study investigates the integration of facial emotion recognition (FER) into Intelligent Tutoring Systems (ITS), with the aim of identifying the emotions that emerge throughout the learning process. Building on prior research, we argue that understanding students’ emotional states enables the delivery of more adaptive and effective feedback, thereby improving learning outcomes. A Deep Convolutional Neural Network (DCNN) was trained on the FER2013+ dataset, achieving a top-3 accuracy of 95.24% in classifying facial expressions across eight emotion categories. The model was integrated with MediaPipe to enable real-time emotion detection from video streams using a standard laptop camera, facilitating practical deployment in educational settings. Thirteen high school and early university students interacted with OATutor—an open-source ITS—while their facial expressions and on-screen activities were recorded. Emotional data from each frame was synchronized with an academic event log documenting actions such as starting a lesson, requesting help, or submitting answers. Results show that “surprise” was the most frequently observed emotion (over 85% of instances), whereas “anger,” “sadness,” and “contempt” appeared only in specific learning scenarios, particularly when students faced cognitive challenges or achieved multiple correct responses. Despite the absence of affective feedback from the system, students’ emotions fluctuated dynamically, suggesting active self-regulation processes. These findings demonstrate the feasibility of FER-enhanced ITS in real-world educational environments and underscore the need for future work integrating multimodal data and personalization strategies to optimize affective responsiveness in intelligent learning contexts. ©The authors ©Springer.
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Sphonic: Development of a Mobile Application Using AI and AR for Learning Biomedical Concepts
(Springer Nature Switzerland, 2025)
Escobar-Castillejos, Daisy
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Báez Gómez Tagle, Enrique Ulises
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Chavarría-Reyes, Fernando Mauricio
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Sigüenza Noriega, Iñaki
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Cruz-Ledesma, Iván
This chapter covers the development of Sphonic, an iOS mobile application that combines artificial intelligence (AI) and augmented reality (AR) to improve biomedical education. Sphonic was designed to employ SwiftUI for its front end, while its back end is based on Django and hosted on Amazon Web Services. Sphonic intends to assist in explaining complex topics in chemistry and biology. Using Apple’s ARKit framework, Sphonic allows students to explore dynamic representations of DNA architecture, chemical bonding interactions, and biological processes to promote engagement and retention. On the other hand, the application features an OCR-based chemical equation solver, using Amazon Bedrock’s generative AI capabilities, that balances equations and offers comprehensive, step-by-step guidance, addressing conceptual deficiencies for learners. Additionally, Sphonic implements secure authentication protocols to protect user data and features a user-friendly interface that simplifies navigation. This chapter concludes by emphasizing the importance of AI and AR in modern education, demonstrating how these technologies could democratize access and understanding of scientific information and foster creativity in academic environments. ©The authors ©Srpinger.
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A Novel Ethical Design Framework Applied to Image Classification Challenges in the Fashion Industry
(Springer Nature Switzerland, 2025)
Guillen Alvarez, Luis
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Martinez-Villaseñor, Lourdes
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Ponce, Hiram
As artificial intelligence (AI) continues to play a pivotal role in image classification applications, the ethical implications of these technologies become increasingly significant. This paper explores the intersection of AI and ethics in the context of image classification, specifically focusing on the application of ethical design principles through a framework for a use of case in the fashion industry involving bags images and social media. This work delves into the integration of a comprehensive ethical framework around all the design process. The case study involves the development and implementation of a neural network tailored for bag image classification, leveraging transfer learning techniques. Through a meticulous examination of the ethical dimensions inherent in image classification, the study aims to establish a foundation for responsible and transparent AI practices. ©The authors ©Springer.
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Leveraging mHealth and Artificial Intelligence for Enhanced Health Indicators, A TwiMV Framework Proposal
(Springer Nature Switzerland, 2025)
Domínguez-Miranda, Sergio Arturo
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Rodríguez Aguilar, Román
Technological advances and artificial intelligence (AI) are transforming healthcare by improving prevention, diagnosis, and remote health monitoring. This paper explores the current landscape of the potential application of digital technologies to the healthcare sector. The design of the TwiMV system is proposed to integrate diverse health data for patient diagnosis and monitoring, in a comprehensive framework, encompassing biochemical studies, genetic analysis, medical images, biometric data, dietary and lifestyle information, and wearable data. The proposal involves real-time processing through cloud-based platforms, as well as the integration of artificial intelligence algorithms and digital technologies. The proposed system aims to improve health management through personalized interventions, with specialized modules addressing priority conditions such as stroke, cardiovascular disease, oncology, diabetes, and neurological disorders. ©The authors ©Springer Nature.
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Artificial Intelligence–Enabled Analysis of Thermography to Diagnose Acute Decompensated Heart Failure
(Elsevier BV, 2025-07)
Atamañuk, Andrés Nicolás
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Gandino, Ignacio Javier
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Miranda, María Noralí
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Cardozo, Leandro Martín
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Escalante, Sergio Exequiel
Background: Analyzing skin temperature in heart failure is an important medical practice that could assist to identify poor perfusion. Thermography, a technique that captures infrared radiation from tissues, could quantify these temperatures and thermal gradients. It has not been evaluated in patients with acute decompensated heart failure (ADHF) before. Objectives: The purpose of this study was to assess the performance of thermography in the diagnosis of ADHF. Methods: A cross-sectional study was performed, including consecutive patients hospitalized with ADHF diagnosed by an expert heart failure team. Patients hospitalized for other cardiac disorders without ADHF were included as controls. Ten thermal photos of each patient were taken within the first 4 hours after admission in a cardiac care unit. Specific thermal spots, averages, and gradients were analyzed. Thermography's diagnostic properties for ADHF detection were evaluated using machine learning with the extreme gradient boosting model. Results: Sixty patients were included: 30 cases with ADHF and 30 controls. The mean age was 63.4 years (SD: 13.3), and 38 (63.3%) were males. Thermal points and averages showed lower temperature, while gradients were higher in the ADHF group, being all statistically significant between groups. The properties of the blend between thermography and artificial intelligence to detect ADHF had 84% sensitivity and 52% specificity. The area under the curve was 0.82 (95% CI: 0.73-0.91). Conclusions: Thermography demonstrated differences between patients with ADHF and those with other cardiological disorders. In this proof of concept, combining thermography with artificial intelligence enabled the detection of ADHF in subjects hospitalized in a cardiac care unit. ©The authors ©JACC: Advances ©Elsevier.
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Preface: Intelligent Computing and Optimization : Proceedings of the 6th International Conference on Intelligent Computing and Optimization 2023 (ICO2023) : Volume 4
(Springer, 2023)
Vasant, Pandian
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Weber, Gerhard-Wilhelm
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Arefin, Mohammad Shamsul
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Rodríguez Aguilar, Román
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Panchenko, Vladimir
The sixth edition of the International Conference on Intelligent Computing and Optimization (ICO’2023) was held during April 27–28, 2023, at G Hua Hin Resort and Mall, Hua Hin, Thailand. The objective of the international conference is to bring the global research scholars, experts and scientists in the research areas of intelligent computing and optimization from all over theworld to share their knowledge and experiences on the current research achievements in these fields. This conference provides a golden opportunity for global research community to interact and share their novel research results, findings and innovative discoveries among their colleagues and friends. The proceedings of ICO’2023 is published by SPRINGER (in the book series Lecture Notes in Networks and Systems) and indexed by SCOPUS. ©2023 Springer, ©2023 The authors.
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Preface: Intelligent Computing and Optimization : Proceedings of the 6th International Conference on Intelligent Computing and Optimization 2023 (ICO2023) : Volume 2
(Springer, 2023)
Pandian Vasant
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Weber, Gerhard-Wilhelm
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Arefin, Mohammad Shamsul
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Rodríguez Aguilar, Román
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Panchenko, Vladimir
The sixth edition of the International Conference on Intelligent Computing and Optimization (ICO’2023) was held during April 27–28, 2023, at G Hua Hin Resort and Mall, Hua Hin, Thailand. The objective of the international conference is to bring the global research scholars, experts and scientists in the research areas of intelligent computing and optimization from all over theworld to share their knowledge and experiences on the current research achievements in these fields. This conference provides a golden opportunity for global research community to interact and share their novel research results, findings and innovative discoveries among their colleagues and friends. The proceedings of ICO’2023 is published by SPRINGER (in the book series Lecture Notes in Networks and Systems) and indexed by SCOPUS. ©2023 Springer, ©2023 The authors.
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Preface: Intelligent Computing and Optimization : Proceedings of the 6th International Conference on Intelligent Computing and Optimization 2023 (ICO2023) : Volume 5
(Springer, 2023)
Vasant, Pandian
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Weber, Gerhard-Wilhelm
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Arefin, Mohammad Shamsul
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Rodríguez Aguilar, Román
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Panchenko, Vladimir
The sixth edition of the International Conference on Intelligent Computing and Optimization (ICO’2023) was held during April 27–28, 2023, at G Hua Hin Resort and Mall, Hua Hin, Thailand. The objective of the international conference is to bring the global research scholars, experts and scientists in the research areas of intelligent computing and optimization from all over theworld to share their knowledge and experiences on the current research achievements in these fields. This conference provides a golden opportunity for global research community to interact and share their novel research results, findings and innovative discoveries among their colleagues and friends. The proceedings of ICO’2023 is published by SPRINGER (in the book series Lecture Notes in Networks and Systems) and indexed by SCOPUS. ©2023 Springer, ©2023 The authors.
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Library Instruction and Research Training in the Context of Artificial Intelligence
(Elsevier, 2024)
Ortiz-Díaz, Erik M
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César Saavedra-alamillas
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Josmel Pacheco-mendoza
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Youness El Hamzaoui
The librarian has played a crucial role throughout history, evolving from a guardian of humanity׳s collective memory to guiding the use of collections and, in recent years, a trainer in the use of information and emerging digital technologies. Currently, the librarian is an active collaborator who understands scientific communication processes and the mechanisms for improving high-impact academic production.
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