id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-017359-zr0bo9el	Pfannschmidt, Karlson	Evaluating Tests in Medical Diagnosis: Combining Machine Learning with Game-Theoretical Concepts	2016-05-10		.txt	text/plain	3335	214	56	Our approach is motivated and illustrated by a concrete case study in veterinary medicine, namely the diagnosis of a disease in cats called feline infectious peritonitis. An important special case is the use of semi-supervised learning to exploit "unlabeled" data coming from individuals for which tests have been made but the true health condition is unknown. Our approach is motivated by a concrete case study in veterinary medicine, namely the diagnosis of a disease in cats called feline infectious peritonitis (FIP). In addition to the use of (semi-supervised) machine learning methodology in medical diagnosis, we propose a game-theoretical approach for measuring the usefulness of individual tests as well as model-based combinations of such tests. More specifically, what can be estimated in this way is the generalization performance of a model that is trained on a combination A and data in the form of L labeled and U unlabeled examples. Performances of different diagnostic tests for feline infectious peritonitis in challenging clinical cases	./cache/cord-017359-zr0bo9el.txt	./txt/cord-017359-zr0bo9el.txt