@article {hicks2022evaluation,
	title = {On evaluation metrics for medical applications of artificial intelligence},
	journal = {Scientific Reports},
	volume = {12},
	number = {1},
	year = {2022},
	pages = {1{\textendash}9},
	publisher = {Nature Publishing Group},
	author = {Hicks, Steven and Str{\"u}mke, Inga and Thambawita, Vajira and Hammou, Malek and Riegler, Michael and Halvorsen, P{\r a}l and Parasa, Sravanthi}
}
@inbook {28006,
	title = {Artificial Intelligence in Gastroenterology},
	booktitle = {Artificial Intelligence in Medicine},
	year = {2021},
	month = {09/2021},
	pages = {1 - 20},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {The holy grail in endoscopy examinations has for a long time been assisted diagnosis using Artificial Intelligence (AI). Recent developments in computer hardware are now enabling technology to equip clinicians with promising tools for computer-assisted diagnosis (CAD) systems. However, creating viable models or architectures, training them, and assessing their ability to diagnose at a human level, are complicated tasks. This is currently an active area of research, and many promising methods have been proposed. In this chapter, we give an overview of the topic. This includes a description of current medical challenges followed by a description of the most commonly used methods in the field. We also present example results from research targeting some of these challenges, and a discussion on open issues and ongoing work is provided. Hopefully, this will inspire and enable readers to future develop CAD systems for gastroenterology.},
	keywords = {Anomaly detection, artificial intelligence, Gastrointestinal endoscopy, Hand-crafted features, Neural Networks, Performance, Semantic segmentation},
	isbn = {978-3-030-58080-3},
	doi = {10.1007/978-3-030-58080-3_163-2},
	url = {https://link.springer.com/referenceworkentry/10.1007\%2F978-3-030-58080-3_163-2},
	author = {Str{\"u}mke, Inga and Hicks, Steven and Thambawita, Vajira and Jha, Debesh and Parasa, Sravanthi and Riegler, Michael and Halvorsen, P{\r a}l},
	editor = {Lidstr{\"o}mer, Niklas and Ashrafian, Hutan}
}
@article {28228,
	title = {MedAI: Transparency in Medical Image Segmentation},
	journal = {Nordic Machine Intelligence},
	volume = {1},
	year = {2021},
	month = {Jan-11-2021},
	pages = {1 - 4},
	publisher = {NMI},
	address = {Oslo},
	doi = {10.5617/nmi.9140},
	url = {https://journals.uio.no/NMI/article/view/9140https://journals.uio.no/NMI/article/download/9140/7753https://journals.uio.no/NMI/article/download/9140/7753},
	author = {Hicks, Steven and Jha, Debesh and Thambawita, Vajira and Halvorsen, P{\r a}l and Singstad, Bj{\o}rn-Jostein and Gaur, Sachin and Pettersen, Klas and Goodwin, Morten and Parasa, Sravanthi and de Lange, Thomas and Riegler, Michael}
}
