Filip Christiansen
Phd Student
E-mail: filip.christiansen.2@ki.se
Visiting address: Södersjukhuset, Sjukhusbacken 21, 11883 Stockholm
Postal address: S1 Klinisk forskning och utbildning, Södersjukhuset, S1 KI SÖS Forskning Kvinnosjukvård Epstein, 118 83 Stockholm
Articles
- Journal article: ULTRASOUND IN OBSTETRICS AND GYNECOLOGY. 2024;64 Suppl 1:2
- Article: ULTRASOUND IN OBSTETRICS AND GYNECOLOGY. 2021;57(1):155-163
- Journal article: ULTRASOUND IN OBSTETRICS AND GYNECOLOGY. 2020;56(S1):8
All other publications
- Published conference paper: LECTURE NOTES IN COMPUTER SCIENCE (INCLUDING SUBSERIES LECTURE NOTES IN ARTIFICIAL INTELLIGENCE AND LECTURE NOTES IN BIOINFORMATICS). 2024;15008:3-12
- Preprint: ELSEVIER BV. 2024
- Book chapter: MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION – MICCAI 2024: LECTURE NOTES IN COMPUTER SCIENCE (INCLUDING SUBSERIES LECTURE NOTES IN ARTIFICIAL INTELLIGENCE AND LECTURE NOTES IN BIOINFORMATICS). 2024;p. 3-12
Employments
- Phd Student, Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, 2024-2027
Distinction and awards
- Trainee Research Prize, Best abstract in Imaging Informatics, Radiological Society of North America, 2024
Journal reviewing
- Ultrasound in Obstetrics & Gynecology, John Wiley & Sons, Anonymous peer review, https://www.webofscience.com/wos/author/record/AAC-6131-2021, 2020
Conference/event participation
- Poster presenter of own accepted abstract, 110th Scientific Assembly and Annual Meeting of the Radiological Society of North America (RSNA), AI-Driven Ultrasound Detection of Ovarian Cancer That Generalizes: An International Multicenter Validation Study, 2024
- Oral presenter of own accepted abstract, ISUOG 34th World Congress on Ultrasound in Obstetrics and Gynecology, https://www.isuog.org/events/past-events/budapest-2024.html, AI-driven ultrasound detection of ovarian cancer that generalizes: an international multicentre validation study, https://doi.org/10.1002/uog.27724, 2024
- Invited speaker, ISUOG 31st World Congress on Ultrasound in Obstetrics and Gynecology, https://www.isuog.org/events/past-events/online-2021.html, Using deep neural networks to classify ovarian pathology, 2021
- Oral presenter of own accepted abstract, ISUOG 30th World Congress on Ultrasound in Obstetrics and Gynecology, https://www.isuog.org/events/past-events/online-2020.html, Ultrasound image analysis using deep neural networks to discriminate benign and malignant ovarian tumours: a comparison to subjective expert assessment, https://doi.org/10.1002/uog.22215, 2020