Alise Danielle Midtfjord
- Machine learning and Data Science
- Explainable Artificial Intelligence
- Applications within risk and safety
I did my Master of Science at the Norwegian University of Life Sciences (NMBU), in Environmental Physics. In my thesis, I combined machine learning with image analysis of PET/CT-images of cancer tumors, to predict the treatment outcome. After that, I worked with technology consulting for Accenture, working with new technologies like machine learning and extended reality. Since August 2019, I have been a PhD Student at the Department of Mathematics at the University of Oslo. Here I am working on modelling and analysis of multidimensional high-resolution environmental data with application to airport runway condition management.
- Midtfjord, Alise Danielle & Huseby, Arne (2020). Estimating Runway Friction Using Flight Data, In Piero Baraldi; Francesco P. Di Maio & Enrico Zio (ed.), e-proceedings of the 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference (ESREL2020 PSAM15). Research Publishing Services. ISBN 9789811485930. Artikkel. Show summary
- Midtfjord, Alise Danielle (2020). Estimating Runway Friction Using Flight Data. Show summary
- Midtfjord, Alise Danielle (2020). Explainable Artificial Intelligence (XAI). Show summary
- Midtfjord, Alise Danielle (2020). Explainable Artificial Intelligence: How to make AI responsible. Show summary
- Grøndahl, Aurora Rosvoll; Midtfjord, Alise Danielle; Langberg, Geir Severin Rakh Elvatun; Tomic, Oliver; Indahl, Ulf Geir; Knudtsen, Ingerid Skjei; Malinen, Eirik; Dale, Einar & Futsæther, Cecilia Marie (2019). Prediction of treatment outcome for head and neck cancers using radiomics of PET/CT images. Radiotherapy and Oncology. ISSN 0167-8140. 133, s 526- 526
- Langberg, Geir Severin; Grøndahl, Aurora Rosvoll; Midtfjord, Alise Danielle; Tomic, Oliver; Liland, Kristian Hovde; Knudtsen, Ingerid Skjei; Dale, Einar; Malinen, Eirik & Futsæther, Cecilia Marie (2019). Establishing a complete radiomics framework for biomarker identification and outcome prediction using PET/CT images of head & neck cancers.