Exploring Aging Research with Natural Language Processing | Aging-US скачать в хорошем качестве

Exploring Aging Research with Natural Language Processing | Aging-US

Aging-US #published this #research paper on November 25, 2025, in Volume 17, Issue 11, titled “A natural language processing–driven map of the aging research landscape" by Jose Perez-Maletzki and Jorge Sanz-Ros from Universidad Europea de Valencia, Faculty of Health Sciences, Department of Physiotherapy, Nutrition and Sports Sciences, Valencia 46010, España; Group of Physical Therapy in the Ageing Process: Social and Health Care Strategies, Department of Physical Therapy, Universitat de València, Valencia 46010, Spain; Department of Pathology, Stanford University School of Medicine, Stanford, CA. ‪@stanford‬ #aging #agingresearch #machinelearning #AI #NLP #paperspotlight #openaccess #openscience #peerreviewed #journal #publishing #meded DOI - https://doi.org/10.18632/aging.206340 Corresponding author - Jorge Sanz-Ros - jsanzros@stanford.edu Abstract Aging research has advanced significantly over the past century, from early studies on animal models to a current emphasis on clinical and translational applications. As research literature expands exponentially, traditional narrative reviews can no longer capture the field’s complexity, highlighting the need for new, unbiased synthesis tools. Here, we leverage advanced natural language processing (NLP) and machine learning (ML) techniques to analyze 461,789 abstracts related to aging published between 1925 and 2023. By integrating Latent Dirichlet Allocation (LDA), term frequency-inverse document frequency (TF-IDF) analysis, dimensionality reduction and clustering, we delineate a comprehensive thematic landscape of aging research. Our results show a clear shift: early decades focused on cellular and molecular mechanisms, while recent years emphasize clinical studies, especially neurodegenerative disorders. Notably, we identify a persistent divide between the biology of aging (BoA) and clinical research, with minimal conceptual overlap between them. Furthermore, we identify distinct clusters representing key biological processes, some of which may have previously been overlooked as cohesive research domains. Finally, we highlight both established and underexplored interconnections that could guide future research. This study outlines shifting priorities and translational gaps in aging research and offers a scalable, data-driven alternative to conventional reviews. Sign up for free Altmetric alerts about this article - https://aging.altmetric.com/details/e... Subscribe for free publication alerts from Aging - https://www.aging-us.com/subscribe-to... Keywords - aging, literature mining, natural language processing, topic modelling, synthesis To learn more about the journal, visit https://www.Aging-US.com​​ and connect with us on social media at: Bluesky - https://bsky.app/profile/aging-us.bsk... ResearchGate - https://www.researchgate.net/journal/... Facebook -   / agingus   X -   / agingjrnl   Instagram -   / agingjrnl   LinkedIn -   / aging   Reddit -   / agingus   Pinterest -   / agingus   YouTube -    / @aging-us   Spotify - https://open.spotify.com/show/1X4HQQg... MEDIA@IMPACTJOURNALS.COM