Library

@article{Yasin2024,

title = {Incorporation of artificial intelligence into nursing research: A scoping review},

author = {Yasin M. Yasin and Areej Al‐Hamad and Kateryna Metersky and Vahe Kehyayan},

doi = {10.1111/inr.13013},

issn = {1466-7657},

year  = {2025},

date = {2025-03-00},

journal = {International Nursing Review},

volume = {72},

number = {1},

publisher = {Wiley},

abstract = {AbstractBackgroundThe integration of artificial intelligence (AI) across different sectors, notably healthcare, is on the rise. However, a thorough exploration of AI's incorporation into nursing research, as well as its advantages and obstacles, is still lacking.ObjectiveThe aim of this scoping review was to map the roles, benefits, challenges, and potentials for the future development and use of AI in the context of nursing research.MethodsAn exhaustive search was conducted across seven databases: MEDLINE, PsycINFO, SCOPUS, Web of Science, CINAHL, Google Scholar, and ProQuest. Articles were additionally identified through manual examination of reference lists of the articles that were included in the study. The search criteria were restricted to articles published in English between 2010 and 2023. The Joanna Briggs Institute (JBI) approach for scoping reviews and the PRISMA‐ScR guidelines guided the processes of source selection, data extraction, and data presentation.ResultsTwenty articles met the inclusion criteria, covering topics from ethical considerations to methodological issues and AI's capabilities in data analysis and predictive modeling.ConclusionThe review identified both the potentials and complexities of integrating AI into nursing research. Ethical and legal considerations warrant a coordinated approach from multiple stakeholders.ImplicationThe findings emphasized AI's potential to revolutionize nursing research, underscoring the need for ethical guidelines, equitable access, and AI literacy training to ensure its responsible and inclusive use.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Cantalejo2025,

title = {Transfering Sustainability Competences through Green Pedagogies and Service-Learning in Higher Education},

author = {María J. Cantalejo and Maite M. Aldaya and Isabel Navarlaz},

url = {https://ecsdev.org/ojs/index.php/ejsd/article/view/1649},

doi = {10.14207/ejsd.2025.v14n1p181},

issn = {2239-6101},

year  = {2025},

date = {2025-02-01},

urldate = {2025-02-01},

journal = {EJSD},

volume = {14},

number = {1},

publisher = {European Center of Sustainable Development},

abstract = {<jats:p>Sustainability competences are reflected in the ability to look ahead to change and shape the future of the societies in which they live through active participation in the sense of sustainable development. Through service-learning, students take responsibility for their actions. The complex nature of sustainability issues makes it useful to explore problems and their solutions holistically.

In the framework of the NEMOS project (A New Educational Model for Acquiring Sustainability Competences through Service-Learning), a collaborative process was initiated to pool the knowledge and experience of five Higher Education Institutions working together to implement new educational models for effectively acquiring sustainability competences through service-learning in food-related degrees. This EU-funded project was launched and aimed to advance the transition to sustainability education through practical and innovative educational approaches and interventions. Green pedagogy can support transformative learning through the exploration and clarification of learners´own values.

In the case of the Public University of Navarre (UPNA), which leads the NEMOS project, practical sessions on service-learning and green pedagogies were held to train university lecturers who teach in different degrees to integrate sustainability in higher education, recognising the relevance of the connection with the environment and the active participation of educators in this process. 

Keywords: Experiential learning, know-how, sustainability education</jats:p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Vishwakarma2023,

title = {Application of artificial intelligence for resilient and sustainable healthcare system: systematic literature review and future research directions},

author = {Laxmi Pandit Vishwakarma and Rajesh Kr Singh and Ruchi Mishra and Archana Kumari},

doi = {10.1080/00207543.2023.2188101},

issn = {1366-588X},

year  = {2025},

date = {2025-01-17},

journal = {International Journal of Production Research},

volume = {63},

number = {2},

pages = {822--844},

publisher = {Informa UK Limited},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Shaw2025,

title = {The Revised Declaration of Helsinki—Considerations for the Future of Artificial Intelligence in Health and Medical Research},

author = {James A. Shaw},

doi = {10.1001/jama.2024.22074},

issn = {0098-7484},

year  = {2025},

date = {2025-01-07},

urldate = {2025-01-07},

journal = {JAMA},

volume = {333},

number = {1},

publisher = {American Medical Association (AMA)},

abstract = {<jats:p>This Viewpoint summarizes recent updates to the Declaration of Helsinki, discusses its relevance in the context of artificial intelligence (AI) in health research, and highlights issues that could affect its future implementation as the use of AI in research increases.</jats:p>},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Seifi2025,

title = {Evaluation and prioritization of artificial intelligence integrated block chain factors in healthcare supply chain: A hybrid Decision Making Approach},

author = {Neda Seifi and Erfan Ghoodjani and Seyed Shabahang Majd and Alireza Maleki and Sayeh Khamoushi},

doi = {10.59543/comdem.v2i.11029},

issn = {3008-1416},

year  = {2025},

date = {2025-01-05},

journal = {COMDEM},

volume = {2},

pages = {374--405},

publisher = {Noroff University College},

abstract = {The integration of artificial intelligence and blockchain in healthcare promises a significant transformation in data management, service quality improvement, and increased patient data security. Blockchain, by offering a decentralized and transparent platform, enhances the reliability and security of information. Meanwhile, artificial intelligence, with its ability to analyse and process data, helps identify patterns and predict treatment outcomes. The aim of this study is Evaluation and prioritization of artificial intelligence integrated blockchain factors in the healthcare supply chain using F-AHP and F-DEMATEL. Following a review of previous studies, four criteria and 23 sub-criteria were identified. In the first step, these criteria were ranked using the F-AHP method. In the second step, relationships among the sub-criteria were determined through F-DEMATEL, identifying causal and effect criteria. The F-AHP results show that among the 23 sub-criteria identified from previous studies, "integration of treatment processes (C32)", "Provide fair service (C31)", "health monitoring (C12)", "security of medical data (C34)", and "clinical decision support (C21)" ranked first to fifth, respectively. The F-DEMATEL results indicate that sub-criteria are divided into causal and effect categories, with "stakeholder participation (C42)" and "technology acceptance (C44)" being the most important causal sub-criteria, while "monitoring the treatment process (C15)" and "patient-centered treatment strategies (C22)" were identified as the most important effect sub-criteria. These findings suggest that the use of AI-blockchain integration in healthcare can lead to significant improvements in managing healthcare systems.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Albisua2025,

title = {Límites éticos en el uso de la inteligencia artificial (IA) en medicina},

author = {Julio Albisua and Pedro Pacheco},

doi = {10.1016/j.opresp.2024.100383},

issn = {2659-6636},

year  = {2025},

date = {2025-01-00},

journal = {Open Respiratory Archives},

volume = {7},

number = {1},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Hanna2025,

title = {Future of Artificial Intelligence (AI) - Machine Learning (ML) Trends in Pathology and Medicine},

author = {Matthew G. Hanna and Liron Pantanowitz and Rajesh Dash and James H. Harrison and Mustafa Deebajah and Joshua Pantanowitz and Hooman H. Rashidi},

doi = {10.1016/j.modpat.2025.100705},

issn = {0893-3952},

year  = {2025},

date = {2025-01-00},

journal = {Modern Pathology},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Shiferaw2024,

title = {Guidelines and standard frameworks for artificial intelligence in medicine: a systematic review},

author = {Kirubel Biruk Shiferaw and Moritz Roloff and Irina Balaur and Danielle Welter and Dagmar Waltemath and Atinkut Alamirrew Zeleke},

doi = {10.1093/jamiaopen/ooae155},

issn = {2574-2531},

year  = {2024},

date = {2024-12-26},

volume = {8},

number = {1},

publisher = {Oxford University Press (OUP)},

abstract = {Abstract

               

                  Objectives

                  The continuous integration of artificial intelligence (AI) into clinical settings requires the development of up-to-date and robust guidelines and standard frameworks that consider the evolving challenges of AI implementation in medicine. This review evaluates the quality of these guideline and summarizes ethical frameworks, best practices, and recommendations.

               

               

                  Materials and Methods

                  The Appraisal of Guidelines, Research, and Evaluation II tool was used to assess the quality of guidelines based on 6 domains: scope and purpose, stakeholder involvement, rigor of development, clarity of presentation, applicability, and editorial independence. The protocol of this review including the eligibility criteria, the search strategy data extraction sheet and methods, was published prior to the actual review with International Registered Report Identifier of DERR1-10.2196/47105.

               

               

                  Results

                  The initial search resulted in 4975 studies from 2 databases and 7 studies from manual search. Eleven articles were selected for data extraction based on the eligibility criteria. We found that while guidelines generally excel in scope, purpose, and editorial independence, there is significant variability in applicability and the rigor of guideline development. Well-established initiatives such as TRIPOD+AI, DECIDE-AI, SPIRIT-AI, and CONSORT-AI have shown high quality, particularly in terms of stakeholder involvement. However, applicability remains a prominent challenge among the guidelines. The result also showed that the reproducibility, ethical, and environmental aspects of AI in medicine still need attention from both medical and AI communities.

               

               

                  Discussion

                  Our work highlights the need for working toward the development of integrated and comprehensive reporting guidelines that adhere to the principles of Findability, Accessibility, Interoperability and Reusability. This alignment is essential for fostering a cultural shift toward transparency and open science, which are pivotal milestone for sustainable digital health research.

               

               

                  Conclusion

                  This review evaluates the current reporting guidelines, discussing their advantages as well as challenges and limitations.

               },

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Molina2024,

title = {What is Spanish regulation on the application of artificial intelligence to medicine like?},

author = {Óscar Andrés Molina and Miriam Jiménez Bernal and Daniel López Wolf and Benjamín Herreros},

doi = {10.1057/s41599-023-02565-2},

issn = {2662-9992},

year  = {2024},

date = {2024-12-00},

journal = {Humanit Soc Sci Commun},

volume = {11},

number = {1},

publisher = {Springer Science and Business Media LLC},

abstract = {AbstractThis article will attempt to analyze the current impact of Artificial Intelligence in Spanish healthcare, as well as the challenges that its application poses both from an ethical and legal point of view. Technological advances, which are already being applied in healthcare, make it necessary to adapt the legal system to the new trends that are emerging in society and force healthcare professionals to review their codes of ethics in the face of new ethical dilemmas, since these codes of ethics do not have clear guidelines for action on AI that raise relevant ethical problems to which no response is being given, except for the code of ethics for medicine, which has recently been included. After a review of the last 5 years of Spanish and European regulations in medicine, it can be concluded that the regulation and legislation of the application of AI is very deficient, both in the EU and in Spain. In order to try to identify different ways of resolving conflicts related to AI in medicine, jurisprudential sentences related to the rights and obligations of health professionals, patients and users have been analyzed and reviewed. Therefore, the paper concludes with the proposal of a series of aspects to be taken into account for the future regulation of the application of AI in medicine.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RibeiroJunior2024,

title = {AI ethics in medical research: the 2024 Declaration of Helsinki},

author = {Howard Lopes Ribeiro Junior},

url = {https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(24)02376-6/fulltext},

doi = {10.1016/s0140-6736(24)02376-6},

issn = {0140-6736},

year  = {2024},

date = {2024-11-00},

urldate = {2024-11-00},

journal = {The Lancet},

volume = {404},

number = {10467},

pages = {2048--2049},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Ritoré2024,

title = {The role of Open Access Data in democratizing healthcare AI: A pathway to research enhancement, patient well-being and treatment equity in Andalusia, Spain},

author = {Álvaro Ritoré and Claudia M. Jiménez and Juan Luis González and Juan Carlos Rejón-Parrilla and Pablo Hervás and Esteban Toro and Carlos Luis Parra-Calderón and Leo Anthony Celi and Isaac Túnez and Miguel Ángel Armengol de la Hoz},

editor = {Po-Chih Kuo},

doi = {10.1371/journal.pdig.0000599},

issn = {2767-3170},

year  = {2024},

date = {2024-09-16},

journal = {PLOS Digit Health},

volume = {3},

number = {9},

publisher = {Public Library of Science (PLoS)},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Basu2024,

title = {Climate change and societal transformation: a cohort-based international experiential learning program with an interdisciplinary focus on environmental education for graduate students},

author = {Onita D. Basu and Diane Isabelle and Stephanie Pineau},

doi = {10.1080/13504622.2024.2390627},

issn = {1469-5871},

year  = {2024},

date = {2024-08-18},

journal = {Environmental Education Research},

pages = {1--23},

publisher = {Informa UK Limited},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Vandemeulebroucke2024,

title = {The ethics of artificial intelligence systems in healthcare and medicine: from a local to a global perspective, and back},

author = {Tijs Vandemeulebroucke},

doi = {10.1007/s00424-024-02984-3},

issn = {1432-2013},

year  = {2024},

date = {2024-07-06},

journal = {Pflugers Arch - Eur J Physiol},

publisher = {Springer Science and Business Media LLC},

abstract = {AbstractArtificial intelligence systems (ai-systems) (e.g. machine learning, generative artificial intelligence), in healthcare and medicine, have been received with hopes of better care quality, more efficiency, lower care costs, etc. Simultaneously, these systems have been met with reservations regarding their impacts on stakeholders’ privacy, on changing power dynamics, on systemic biases, etc. Fortunately, healthcare and medicine have been guided by a multitude of ethical principles, frameworks, or approaches, which also guide the use of ai-systems in healthcare and medicine, in one form or another. Nevertheless, in this article, I argue that most of these approaches are inspired by a local isolationist view on ai-systems, here exemplified by the principlist approach. Despite positive contributions to laying out the ethical landscape of ai-systems in healthcare and medicine, such ethics approaches are too focused on a specific local healthcare and medical setting, be it a particular care relationship, a particular care organisation, or a particular society or region. By doing so, they lose sight of the global impacts ai-systems have, especially environmental impacts and related social impacts, such as increased health risks. To meet this gap, this article presents a global approach to the ethics of ai-systems in healthcare and medicine which consists of five levels of ethical impacts and analysis: individual-relational, organisational, societal, global, and historical. As such, this global approach incorporates the local isolationist view by integrating it in a wider landscape of ethical consideration so to ensure ai-systems meet the needs of everyone everywhere.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{TheLancetPlanetaryHealth2024b,

title = {A risky business},

author = { The Lancet Planetary Health},

doi = {10.1016/s2542-5196(24)00011-1},

issn = {2542-5196},

year  = {2024},

date = {2024-02-00},

journal = {The Lancet Planetary Health},

volume = {8},

number = {2},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Vonderschmidt2024,

title = {Analysis combining the multiple FAO food balance sheet datasets needs careful treatment},

author = {Alexander Vonderschmidt and Bartlomiej Arendarczyk and Lindsay M Jaacks and Alexandra L Bellows and Peter Alexander},

doi = {10.1016/s2542-5196(23)00276-0},

issn = {2542-5196},

year  = {2024},

date = {2024-02-00},

journal = {The Lancet Planetary Health},

volume = {8},

number = {2},

pages = {e69--e71},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Brisbois2024,

title = {Learning from the lobster and making space for transformation in planetary health},

author = {Ben Brisbois and Katrina M Plamondon},

doi = {10.1016/s2542-5196(24)00002-0},

issn = {2542-5196},

year  = {2024},

date = {2024-02-00},

journal = {The Lancet Planetary Health},

volume = {8},

number = {2},

pages = {e72--e73},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Trasande2024,

title = {Prenatal phthalate exposure and adverse birth outcomes in the USA: a prospective analysis of births and estimates of attributable burden and costs},

author = {Leonardo Trasande and Morgan E Nelson and Akram Alshawabkeh and Emily S Barrett and Jessie P Buckley and Dana Dabelea and Anne L Dunlop and Julie B Herbstman and John D Meeker and Mrudula Naidu and Craig Newschaffer and Amy M Padula and Megan E Romano and Douglas M Ruden and Sheela Sathyanarayana and Susan L Schantz and Anne P Starling and Ghassan B Hamra and PB Smith and KL Newby and LP Jacobson and DJ Catellier and R Gershon and D Cella and J Cordero and F Tylavsky and A Mason and Q Zhao and N Bush and KZ LeWinn and K Lyall and H Volk and R Schmidt and JM Kerver and C Barone and C Fussman and N Paneth and M Elliott and R Nguyen and S Swan and C Karr},

doi = {10.1016/s2542-5196(23)00270-x},

issn = {2542-5196},

year  = {2024},

date = {2024-02-00},

journal = {The Lancet Planetary Health},

volume = {8},

number = {2},

pages = {e74--e85},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Madaniyazi2024,

title = {Seasonality of mortality under climate change: a multicountry projection study},

author = {Lina Madaniyazi and Ben Armstrong and Aurelio Tobias and Malcolm N Mistry and Michelle L Bell and Aleš Urban and Jan Kyselý and Niilo Ryti and Ivana Cvijanovic and Chris Fook Sheng Ng and Dominic Roye and Ana Maria Vicedo-Cabrera and Shilu Tong and Eric Lavigne and Carmen Íñiguez and Susana das Neves Pereira da Silva and Joana Madureira and Jouni J K Jaakkola and Francesco Sera and Yasushi Honda and Antonio Gasparrini and Masahiro Hashizume and Rosana Abrutzky and Fiorella Acquaotta and Barrak Alahmad and Antonis Analitis and Hanne Krage Carlsen and Gabriel Carrasco-Escobar and Micheline de Sousa Zanotti Stagliorio Coelho and Valentina Colistro and Patricia Matus Correa and Tran Ngoc Dang and Francesca de'Donato and Magali Hurtado Diaz and Do Van Dung and Alireza Entezari and Bertil Forsberg and Patrick Goodman and Yue Leon Guo and Yuming Guo and Iulian-Horia Holobaca and Danny Houthuijs and Veronika Huber and Ene Indermitte and Haidong Kan and Klea Katsouyanni and Yoonhee Kim and Ho Kim and Whanhee Lee and Shanshan Li and Fatemeh Mayvaneh and Paola Michelozzi and Hans Orru and Nicolás Valdés Ortega and Samuel Osorio and Ala Overcenco and Shih-Chun Pan and Mathilde Pascal and Martina S. Ragettli and Shilpa Rao and Raanan Raz and Paulo Hilario Nascimento Saldiva and Alexandra Schneider and Joel Schwartz and Noah Scovronick and Xerxes Seposo and César De la Cruz Valencia and Antonella Zanobetti and Ariana Zeka},

doi = {10.1016/s2542-5196(23)00269-3},

issn = {2542-5196},

year  = {2024},

date = {2024-02-00},

journal = {The Lancet Planetary Health},

volume = {8},

number = {2},

pages = {e86--e94},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}