Deep learning-based infrared thermography reveals reproducible uniform and individual thermoregulatory responses during running.
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| Title: | Deep learning-based infrared thermography reveals reproducible uniform and individual thermoregulatory responses during running. |
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| Authors: | Weber V; Department of Sports Medicine, Disease Prevention and Rehabilitation, Institute of Sports Science, Faculty of Social Science, Media and Sports, Johannes Gutenberg University, Mainz, Germany., López DA; Institute of Computer Science, Research Group Computational Geometry, Johannes Gutenberg University, Mainz, Germany., Ochmann DT; Department of Sports Medicine, Disease Prevention and Rehabilitation, Institute of Sports Science, Faculty of Social Science, Media and Sports, Johannes Gutenberg University, Mainz, Germany., Zentgraf S; Department of Sports Medicine, Disease Prevention and Rehabilitation, Institute of Sports Science, Faculty of Social Science, Media and Sports, Johannes Gutenberg University, Mainz, Germany., Nägele M; Optoprecision GmbH, Bremen, Germany., Neuberger EWI; Department of Sports Medicine, Disease Prevention and Rehabilitation, Institute of Sports Science, Faculty of Social Science, Media and Sports, Johannes Gutenberg University, Mainz, Germany., Schömer E; Institute of Computer Science, Research Group Computational Geometry, Johannes Gutenberg University, Mainz, Germany., Simon P; Department of Sports Medicine, Disease Prevention and Rehabilitation, Institute of Sports Science, Faculty of Social Science, Media and Sports, Johannes Gutenberg University, Mainz, Germany., Hillen B; Department of Sports Medicine, Disease Prevention and Rehabilitation, Institute of Sports Science, Faculty of Social Science, Media and Sports, Johannes Gutenberg University, Mainz, Germany. b.hillen@uni-mainz.de.; Institute of Occupational, Social, and Environmental Medicine, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany. b.hillen@uni-mainz.de. |
| Source: | Scientific reports [Sci Rep] 2026 Mar 28; Vol. 16 (1). Date of Electronic Publication: 2026 Mar 28. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 2045-2322 |
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| DOI: | 10.1038/s41598-026-44102-6 |
