Marta Quemada Lopez

• Lopez, Marta Quemada; Plagemann, Thomas Peter; Goebel, Vera Hermine; Adams, Jonathan; Hui, David & Øverland, Britt [Vis alle 8 forfattere av denne artikkelen] (2024). Requirements Analysis for Responsible Explainable AI for Pediatric Sleep Apnea Diagnosis. I Pesch, Dirk (Red.), Proceeding IEEE International Conference on Smart Computing 2024. IEEE (Institute of Electrical and Electronics Engineers). ISSN 9798350349948. s. 362–367. doi: 10.1109/SMARTCOMP61445.2024.00082. Fulltekst i vitenarkiv Vis sammendrag

  This paper presents a novel approach to requirements engineering for responsible explainable AI (rexAI) that pays attention to the broad range of explanation aspects and enforces the consideration of computer science, ethical, legal, and medical requirements. The medical use-case we are investigating is pediatric sleep apnea diagnosis. We analyze the non-functional and functional requirements and explore the multiple relationships and dependencies between the rexAI requirements and principles.

Se alle arbeider i NVA

• Lopez, Marta Quemada (2024). Uncertainty Quantification in Deep Learning Models for Sleep Apnea Detection. Fulltekst i vitenarkiv
• Lopez, Marta Quemada; Plagemann, Thomas Peter; Goebel, Vera Hermine; Adams, Jonathan; Hui, David & Øverland, Britt [Vis alle 8 forfattere av denne artikkelen] (2024). Requirements Analysis for Responsible Explainable AI for Pediatric Sleep Apnea Diagnosis. Fulltekst i vitenarkiv

Se alle arbeider i NVA