Medical applications in case-based reasoning

By A. Holt, I. Bichindaritz, Rainer Schmidt, P. Perner. 2005

234 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

This looks like that: deep learning for interpretable image recognition (2018, background): “, radiologists compare suspected tumors in X-ray scans with prototypical tumor images for diagnosis of cancer [13].”
Deep Bayesian Hashing with Center Prior for Multi-modal Neuroimage Retrieval (2020, background): “In practice, it is important to provide physicians with previous cases (with visually similar neuroimages) and their corresponding treatment records to facilitate case-based reasoning and evidence-based medicine in clinical decision making [19], [20].”
Content-Based Medical Image Retrieval: A Survey of Applications to Multidimensional and Multimodality Data (2013, background): “The question of image similarity has important applications in the medical domain because diagnostic decision-making has traditionally involved using evidence from a patient’s data (image and nonimage) coupled with the physician’s prior experiences of similar cases [4].”
Retrieval, reuse, revision and retention in case-based reasoning (2005, unknown): “This has given rise to a number of medical CBR systems that support this type of decision making (Holt et al., 2005).See Kolodner (1994)and Leake (1998) for more extensive discussions of CBR as a cognitive model.”