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Here, the development of a photonic technology for monitoring perinatal asphyxia is presented and validated in vivo in a preclinical stage. Contrary to state of the art, the technology provides continuous data in real\u2010time in a non\u2010invasive manner. Moreover, the technology does not rely on a single parameter as pH or lactate, instead monitors changes of the entirety of physiological parameters accessible by Raman spectroscopy. By a fiber\u2010coupled Raman probe that is in controlled contact with the skin of the subject, near\u2010infrared Raman spectra are measured and analyzed by machine learning algorithms to develop classification models. As a performance benchmarking, various hybrid and non\u2010hybrid classifiers are tested. In an asphyxia model in newborn pigs, more than 1000 Raman spectra are acquired at three different clinical phases\u2014basal condition, hypoxia\u2013ischemia, and post\u2010hypoxia\u2013ischemia stage. In this preclinical proof\u2010of\u2010concept study, figures\u00a0of merit reach 90% levels for classifying the clinical phases and demonstrate the power of the technology as an innovative medical tool for diagnosing a perinatal adverse\u00a0outcome.<\/jats:p>","DOI":"10.1002\/advs.202204834","type":"journal-article","created":{"date-parts":[[2022,11,15]],"date-time":"2022-11-15T03:40:30Z","timestamp":1668483630000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Photonic Technology for In Vivo Monitoring of Hypoxia\u2013Ischemia"],"prefix":"10.1002","volume":"10","author":[{"given":"Ion","family":"Olaetxea","sequence":"first","affiliation":[{"name":"CIC nanoGUNE BRTA San Sebasti\u00e1n 20018 Spain"},{"name":"Department of Communications Engineering University of the Basque Country Bilbao 48013 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