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This research paper presents a modified Needleman–Wunsch algorithm aimed at improving clinical pathway clustering by integrating expert knowledge with data. The new distance metric enhances clustering results for lung cancer pathways by providing contextual information, addressing limitations of existing metrics. The study utilizes a dataset of 2350 lung cancer referrals and discusses the implications of the findings for healthcare delivery and decision support tools.
- Author
- balaji xerox
- Language
- EN