This paper is in the following e-collection/theme issue:

Scoping Review Protocols (253) Methods in Cancer Research (54) Clinical Informatics (1335) Data Science (360) Decision Support for Health Professionals (1555) Information Retrieval (352)

Published on in Vol 13 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/58705, first published .
Identifications of Similarity Metrics for Patients With Cancer: Protocol for a Scoping Review

Identifications of Similarity Metrics for Patients With Cancer: Protocol for a Scoping Review

Identifications of Similarity Metrics for Patients With Cancer: Protocol for a Scoping Review

Authors of this article:

Iryna Manuilova1, 2 Author Orcid Image ;   Jan Bossenz1 Author Orcid Image ;   Annemarie Bianka Weise1 Author Orcid Image ;   Dominik Boehm3, 4 Author Orcid Image ;   Cosima Strantz5 Author Orcid Image ;   Philipp Unberath3, 6 Author Orcid Image ;   Niklas Reimer7, 8, 9 Author Orcid Image ;   Patrick Metzger10, 11 Author Orcid Image ;   Thomas Pauli10 Author Orcid Image ;   Silke D Werle12 Author Orcid Image ;   Susann Schulze13 Author Orcid Image ;   Sonja Hiemer13 Author Orcid Image ;   Arsenij Ustjanzew14 Author Orcid Image ;   Hans A Kestler12 Author Orcid Image ;   Hauke Busch7, 8 Author Orcid Image ;   Benedikt Brors15, 16, 17, 18 Author Orcid Image ;   Jan Christoph1, 2, 5 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Manuilova I, Bossenz J, Weise A, Boehm D, Döbel M, Werle S, Ustjanzew A, Reimer N, Strantz C, Unberath P, Metzger P, Pauli T, Schulze S, Hiemer S, Oguztürk I, Kamkar L, Kestler H, Busch H, Brors B, Christoph J. Uncovering the Understanding of the Concept of Patient Similarity in Cancer Research and Treatment: Scoping Review. Journal of Medical Internet Research 2025;27:e71906 View

Conference Proceedings

  1. Al Musawi A, Rana P, Raha S, Braunstein J, Sleeman W, Kapoor R, Ghosh P. Proceedings of the 16th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics. ICU-Length of Stay Prediction on Electronic Health Records using Graph Neural Networks and Homogeneous Similarity Graphs View