Technical and regulatory challenges in artificial intelligence-based pulse oximetry: a proposed development pipeline

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dc.catalogadorpva
dc.contributor.authorCabanas, Ana M.
dc.contributor.authorMartín-Escudero, Pilar
dc.contributor.authorPagan, Josué
dc.contributor.authorMery Quiroz, Domingo
dc.date.accessioned2025-04-28T19:27:08Z
dc.date.available2025-04-28T19:27:08Z
dc.date.issued2025
dc.description.abstractPulse oximetry, although generally effective under ideal conditions, faces challenges in accurately estimating peripheral oxygen saturation (SpO2) in complex clinical scenarios, particularly at lower saturation levels and in patients with darker skin pigmentation. Artificial intelligence (AI) offers the potential to improve SpO2 monitoring by enabling more accurate, equitable, and accessible estimations. We highlight key challenges in developing AI-enhanced pulse oximetry, including the need for diverse and representative datasets, refined validation protocols addressing ethical concerns such as algorithmic bias, expanded SpO2 measurement ranges encompassing hypoxaemic levels, and enhanced model interpretability. We emphasise the importance of transitioning from subjective skin tone assessments to quantitative methods to ensure equity and mitigate bias. Finally, we propose a development pipeline and discuss strategies for robust, fair AI-based SpO2 monitoring, including aligning validation with global regulatory frameworks and fostering interdisciplinary collaboration. These advances will improve the reliability and fairness of pulse oximetry, ultimately contributing to enhanced global patient care.
dc.description.funderFondecyt
dc.description.funderNational Center for Artificial Intelligence CENIA
dc.description.funderANID
dc.description.funderUTA
dc.format.extent5 páginas
dc.fuente.origenORCID
dc.identifier.doi10.1016/j.bja.2025.02.014
dc.identifier.eissn1471-6771
dc.identifier.issn0007-0912
dc.identifier.scopusidSCOPUS_ID:105000043497
dc.identifier.urihttps://doi.org/10.1016/j.bja.2025.02.014
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/103493
dc.information.autorucEscuela de Ingeniería; Mery Quiroz, Domingo; 0000-0003-4748-3882; 102382
dc.issue.numero5
dc.language.isoen
dc.nota.accesocontenido parcial
dc.pagina.final1299
dc.pagina.inicio1295
dc.publisherElsevier Ltd.
dc.revistaBritish Journal of Anaesthesia
dc.rightsacceso restringido
dc.subjectArtificial intelligence
dc.subjectBias
dc.subjectHaemoglobin oxygen saturation
dc.subjectPulse oximetry
dc.subjectRegulation
dc.subjectSkin pigmentation
dc.subject.ddc610
dc.subject.deweyMedicina y saludes_ES
dc.subject.ods03 Good health and well-being
dc.subject.odspa03 Salud y bienestar
dc.titleTechnical and regulatory challenges in artificial intelligence-based pulse oximetry: a proposed development pipeline
dc.typeeditorial
dc.volumen134
sipa.codpersvinculados102382
sipa.trazabilidadORCID;2025-04-21
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