Decoding the reproductive microbiome: enabling clinical and biological insights through machine and deep learning.

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Bibliographic Details
Title: Decoding the reproductive microbiome: enabling clinical and biological insights through machine and deep learning.
Authors: Garach Vélez I; Department of Computer Engineering, Automatics and Robotics, CITIC, University of Granada, Granada, Spain., Leonés-Baños I; Department of Biochemistry and Molecular Biology, Faculty of Sciences, University of Granada, Granada, Spain.; Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain., Folch BA; Department of Biochemistry and Molecular Biology, Faculty of Sciences, University of Granada, Granada, Spain.; Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain., Antequera L; Department of Computer Engineering, Automatics and Robotics, CITIC, University of Granada, Granada, Spain., Rojas I; Department of Computer Engineering, Automatics and Robotics, CITIC, University of Granada, Granada, Spain., Ortuño F; Department of Computer Engineering, Automatics and Robotics, CITIC, University of Granada, Granada, Spain., Lara MJS; Department of Biochemistry and Molecular Biology, Faculty of Sciences, University of Granada, Granada, Spain.; Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain., Altmäe S; Division of Obstetrics and Gynecology, Department of Clinical Science, Intervention and Technology CLINTEC, Karolinska Institutet, Stockholm, Sweden.; Department of Gynecology and Reproductive Medicine, Karolinska University Hospital, Huddinge, Stockholm, Sweden.; Department of Biochemistry and Molecular Biology, Faculty of Sciences, University of Granada, Granada, Spain.; Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain., Herrera LJ; Department of Computer Engineering, Automatics and Robotics, CITIC, University of Granada, Granada, Spain.; Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain.
Source: Frontiers in endocrinology [Front Endocrinol (Lausanne)] 2026 Jun 15; Vol. 17, pp. 1812407. Date of Electronic Publication: 2026 Jun 15 (Print Publication: 2026).
Publication Type: Journal Article; Review; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Frontiers Research Foundation] Country of Publication: Switzerland NLM ID: 101555782 Publication Model: eCollection Cited Medium: Print ISSN: 1664-2392 (Print) Linking ISSN: 16642392 NLM ISO Abbreviation: Front Endocrinol (Lausanne) Subsets: MEDLINE
Database: MEDLINE Ultimate
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