Abstract
In order to deal with enormous unstructured healthcare data, it becomes paramount to develop efficient tools for retrieval of useful data subject to a query posed by entities. The entity can be a doctor, nurse, patient, or relative. Uncertainty, imprecision, and incompleteness arise from various forms and are present when a query is posed to the unstructured database. A popular technique for information retrieval is Fuzzy Logic-based information retrieval. Primarily, the Mamdani Fuzzy Inference Engine is used for ranking the documents based on the query. Recently, Neutrosophic Logic was proposed for efficient handling of data which is uncertain, incomplete, and imprecise. This research aims to validate the effectiveness of Neutrosophic Logic for healthcare document retrieval using Neutrosophic Logic and analyze its merit or demerit over the traditional Fuzzy Logic-based retrieval strategy. The experimental results confirm efficiency measured in terms of MSE scores. The proposed work has been validated for cancer-related healthcare documents.
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Sinha, S.K., Kumar, C. (2020). Healthcare Information Retrieval Based on Neutrosophic Logic. In: Agarwal, S., Verma, S., Agrawal, D. (eds) Machine Intelligence and Signal Processing. MISP 2019. Advances in Intelligent Systems and Computing, vol 1085. Springer, Singapore. https://doi.org/10.1007/978-981-15-1366-4_18
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DOI: https://doi.org/10.1007/978-981-15-1366-4_18
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