Details der Publikation - A comprehensive decision support model for online doctors ranking with interval-valued neutrosophic numbers

A comprehensive decision support model for online doctors ranking with interval-valued neutrosophic numbers / Pei Liang, Junhua Hu, KwaiSang Chin

Medienart:	E-Artikel

Erscheinungsjahr:	2024
Erschienen:	2024

Enthalten in:	Zur Gesamtaufnahme - volume:31
Enthalten in:	International transactions in operational research - 31(2024), 4 vom: Juli, Seite 2504-2527

Sprache:	Englisch

Beteiligte Personen:	Liang, Pei [VerfasserIn] Hu, Junhua [VerfasserIn] Chin, KwaiSang [VerfasserIn]

Links:	onlinelibrary.wiley.com [lizenzpflichtig] doi.org [lizenzpflichtig]

Themen:	Doctors ranking Homogeneity Interval-valued neutrosophic numbers Multi-criteria Text mining

doi:	10.1111/itor.13208

funding:
Förderinstitution / Projekttitel:

PPN (Katalog-ID):	1885743521

Internformat


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912			\|a GBV_ILN_2027
912			\|a GBV_ILN_2031
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912			\|a GBV_ILN_2037
912			\|a GBV_ILN_2038
912			\|a GBV_ILN_2039
912			\|a GBV_ILN_2044
912			\|a GBV_ILN_2048
912			\|a GBV_ILN_2049
912			\|a GBV_ILN_2050
912			\|a GBV_ILN_2055
912			\|a GBV_ILN_2056
912			\|a GBV_ILN_2057
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912			\|a GBV_ILN_2472
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952			\|d 31 \|j 2024 \|e 4 \|c 7 \|h 2504-2527
980			\|2 26 \|1 01 \|x 0206 \|b 4511660778 \|y x1z \|z 15-04-24
982			\|2 26 \|1 00 \|x DE-206 \|b Web-based appointment systems are emerging in the healthcare industry with mass data, but homogenized online information and poor evaluation criteria lead to blindness in selecting doctors. To select an appropriate doctor when making appointments online, a comprehensive decision support model is proposed. First, one class of multi-criteria is built from reviews by text mining technologies. For quantitative analysis, interval-valued neutrosophic numbers (IVNNs) are utilized to describe reviews, and related integration operators of IVNNs are employed. Second, another class of multi-criteria is established by the website-given labels. A disease similarity measure-based transformation method is proposed to redefine the doctors’ specialization, making the evaluation values more discriminable. Finally, a personalized doctor ranking result is derived by integrating the two classes of multi-criteria values with a preference parameter. A case study of Wedoctor.com is conducted to validate the proposed model, and the comparison result indicates that the model can effectively support users’ decision-making.

A comprehensive decision support model for online doctors ranking with interval-valued neutrosophic numbers / Pei Liang, Junhua Hu, KwaiSang Chin

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