2026-09-14T12:40:28Zhttps://gredos.usal.es/oai/request

oai:gredos.usal.es:10366/1531562025-04-30T20:36:59Zcom_10366_122575com_10366_4512com_10366_3823col_10366_134243

Canal-Alonso, Ángel Jiménez, Pedro Egido, Noelia Prieto Tejedor, Javier Corchado Rodríguez, Juan Manuel 2023-10-04T11:40:55Z 2023-10-04T11:40:55Z 2022 http://hdl.handle.net/10366/153156 [EN]DNA sequencing is one of the fields that has advanced the most in recent years within clinical genetics and human biology. However, the large amount of data generated through next generation sequencing (NGS) techniques requires advanced data analysis processes that are sometimes complex and beyond the capabilities of clinical staff. Therefore, this work aims to shed light on the possibilities of applying hybrid algorithms and explainable artificial intelligence (XAI) to data obtained through NGS. The suitability of each architecture will be evaluated phase by phase in order to offer final recommendations that allow implementation in clinical sequencing workflows eng info:eu-repo/semantics/openAccess Next-Generation sequencing Explainable Artificial Intelligence Hybrid Algorithms Application of hybrid algorithms and Explainable Artificial Intelligence ingenomic sequencing info:eu-repo/semantics/article