Saul Fuster Navarro | Universitetet i Stavanger

Kontakt

Rom: KE E-401

Organisasjonsenhet

Det teknisk- naturvitenskapelige fakultet

Institutt for data- og elektroteknologi

Kort om meg

Saul Fuster Navarro is currently employed as a post-doctoral researcher at the Department of Electrical Engineering and Computer Science (TN-IDE). Currently, he works under the NewbornTime project for newborn resuscitation video activity recognition in collaboration with Stavanger University Hospital and Laerdal Medical. He completed a Ph.D. in Science and Technology at UiS in 2024, on the topic of developing computer vision artificial intelligence algorithms for histopathological images of bladder cancer. The work carried out during the PhD period was funded under a Horizon 2020 Marie Curie grant. Also, he completed his B.Sc. and Master of Telecommunications Engineering from Universitat Politècnica de València, Spain, in 2017 and 2019 respectively.

Dette forsker jeg på

Under the NewbornTime project, he aims to develop a deep learning model for video activity recognition of resuscitation episodes of newborn. The main objective is to combine the model's predictions with the estimated time of birth to create a timeline that includes all activities from birth to the subsequent resuscitation.

Akademisk bakgrunn

His research interests are in artificial intelligence algorithms particularly with computer vision.

Følg meg på nett

Publikasjoner

Vitenskapelige publikasjoner

Saul Fuster Navarro; Farbod Khoraminia; Julio Silva-Rodríguez; Umay Kiraz; Geert J. L. H. van Leenders; Trygve Christian Eftestøl; Valery Naranjo; Emiel Janssen; Tahlita C. M. Zuiverloon; Kjersti Engan (2025) Self-contrastive weakly supervised learning framework for prognostic prediction using whole slide images. I: PLOS Digital Health. Online ISSN 2767-3170. Volum 4. DOI: 10.1371/journal.pdig.0000972

Saul Fuster Navarro; Kjersti Engan; Trygve Christian Eftestøl (2024) Deep Learning-Driven Diagnostic and Prognostic Solutions for Histopathological Images of Bladder Cancer. Universitetet i Stavanger. ISBN 9788284392417.

Marie Bø-Sande; Edvin Benjaminsen; Neel Kanwal; Saul Fuster Navarro; Helga Hardardottir; Ingrid Lundal; Emiel Janssen; Kjersti Engan (2024) A Dual Convolutional Neural Network Pipeline for Melanoma Diagnostics and Prognostics. I: Proceedings of Machine Learning Research (PMLR). Online ISSN 2640-3498. s.20-26. DOI: https://proceedings.mlr.press/v233/bo-sande24a.html

Saul Fuster Navarro; Umay Kiraz; Trygve Christian Eftestøl; Emiel Janssen; Kjersti Engan (2024) NMGrad: Advancing Histopathological Bladder Cancer Grading with Weakly Supervised Deep Learning. I: Bioengineering. Online ISSN 2306-5354. Volum 11. DOI: 10.3390/bioengineering11090909

Farbod Khoraminia; Saul Fuster Navarro; Neel Kanwal; Mitchell Olislagers; Kjersti Engan; Geet J.L.H. Van Leenders; Andrew P Stubbs; Farhan Akram; Tahlita C.M. Zuiverloon (2023) Artificial Intelligence in Digital Pathology for Bladder Cancer: Hype or Hope? A Systematic Review. I: Cancers. Online ISSN 2072-6694. Volum 15. s.4518-4518. DOI: 10.3390/cancers15184518

Christopher Andreassen; Saul Fuster Navarro; Helga Hardardottir; Emiel Janssen; Kjersti Engan (2023) Deep Learning for Predicting Metastasis on Melanoma Wsis. I: IEEE International Symposium on Biomedical Imaging. ISSN 1945-7928. DOI: 10.1109/ISBI53787.2023.10230474

Saul Fuster Navarro; Farbod Khoraminia; Trygve Christian Eftestøl; Tahlita C M Zuiverloon; Kjersti Engan (2023) Active Learning Based Domain Adaptation for Tissue Segmentation of Histopathological Images. I: European Signal Processing Conference. ISSN 2076-1465. s.1045-1049. DOI: 10.23919/EUSIPCO58844.2023.10290058

Saul Fuster Navarro; Trygve Christian Eftestøl; Kjersti Engan (2022) Nested multiple instance learning with attention mechanisms. I: . IEEE, Proceedings 21st IEEE international conference on machine learning and applications : ICMLA 2022. IEEE (Institute of Electrical and Electronics Engineers). ISBN 9781665462839. s.220-225. DOI: 10.1109/ICMLA55696.2022.00038

Saul Fuster Navarro; Farbod Khoraminia; Umay Kiraz; Neel Kanwal; Vebjørn Kvikstad; Trygve Christian Eftestøl; Tahlita C M Zuiverloon; Emiel Janssen; Kjersti Engan (2022) Invasive cancerous area detection in non-muscle invasive bladder cancer whole slide images. I: . IEEE, 2022 IEEE 14th image video and multidimensional signal processing workshop (IVMSP) : 26-29 June 2022 : Nafplio, Greece. IEEE (Institute of Electrical and Electronics Engineers). ISBN 9781665478229. DOI: 10.1109/IVMSP54334.2022.9816352

Neel Kanwal; Saul Fuster Navarro; Farbod Khoraminia; Tahlita C M Zuiverloon; Rong Chunming; Kjersti Engan (2022) Quantifying the effect of color processing on blood and damaged tissue detection in Whole Slide Images. I: . IEEE, 2022 IEEE 14th image video and multidimensional signal processing workshop (IVMSP) : 26-29 June 2022 : Nafplio, Greece. IEEE (Institute of Electrical and Electronics Engineers). ISBN 9781665478229. DOI: 10.1109/IVMSP54334.2022.9816283

Formidling

Saul Fuster Navarro; Trygve Christian Eftestøl; Kjersti Engan (2022) Nested Multiple Instance Learning with Attention Mechanisms. ICMLA 2022; 2022-12-12 - 2022-12-14.

Saul Fuster Navarro; Trygve Christian Eftestøl; Kjersti Engan; Umay Kiraz; Vebjørn Kvikstad; Emiel Janssen (2022) Invasive Cancerous Area Detection in Non-Muscle Invasive Bladder Cancer Whole Slide Images. IVMSP 2022; 2022-06-26 - 2022-06-29.

Saul Fuster Navarro; Trygve Christian Eftestøl; Kjersti Engan; Umay Kiraz; Emiel Janssen; Vebjørn Kvikstad (2022) Towards Automatic Staging of NonMuscle Invasive Bladder Cancer. hAIST 22; 2022-06-13 - 2022-06-14.

Saul Fuster Navarro; Trygve Christian Eftestøl; Kjersti Engan; Umay Kiraz; Emiel Janssen; Vebjørn Kvikstad (2022) Towards Automatic Staging of Non-Muscle Invasive Bladder Cancer. NORA 2022; 2022-06-09 - 2022-06-10.

Kjersti Engan; Rune Wetteland; Saul Fuster Navarro; Neel Kanwal (2022) Examples of artificial intelligence in computational pathology. hAIst Conference – Health-related Artificial Intelligence in Stavanger; 2022-06-13 - 2022-06-14.

Saul Fuster Navarro; Kjersti Engan; Trygve Christian Eftestøl (2021) A Nested Multiple Instance Learning Framework. NOBIM 2021; 2021-09-13 - 2021-09-14.

Kilde: Nasjonalt vitenarkiv