An Interrelated Decision-Making Model for an Intelligent Decision Support System in Healthcare
نویسندگان
چکیده
The nature of decision making in healthcare is complex and crucial. It essential to have a tool that helps with accurate correct decisions based on real-time data. Moreover, the process itself complex, comprising various stages from primary palliative, closely related each other, different depending type disease. Each stage has crucial be made relying other stages’ decisions. Thus, an intelligent support system (IDSS) model data mining approach becomes prominent solution. However, existing IDSS Group Decision Support System (GDSS) applied single-stage primarily focused development at certain for specific outcomes. In contrast, decision-making previous stages, which change dynamically. Therefore, this paper proposes interrelated (IDM) aims effective by utilizing knowledge following treatment known as IDM-IDSS-healthcare. experiment was conducted using simulated diabetes treatments were validated medical expert. Eight sets distinct sizes constructed classified into two types categories. consists secondary care range 25 58 attributes 300-11,000 instances. results show algorithms J48, Logistic, NaiveBayes Updateable, RandomTree, BayesNet AdaBoostM1 obtained best accuracy sequence 46% 99%. result also shows improvement efficiency prediction increased up 56%. addition, all respondents agreed focus-group discussion information technology (IT) experts proposed IDM-IDSS-healthcare practical solution should use multi-agent approach.
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2022
ISSN: ['2169-3536']
DOI: https://doi.org/10.1109/access.2022.3160725