## 4 Results and Discussion
### High-Quality Papers Details
\begin{table}
\begin{tabular}{l l l l l} \hline \hline
**Citation** & **Short Description** & **Year** & **Application Domain** & **Quality** \\ \hline
[102] & Decision support system based on a three-layer model for improving accuracy prediction in comparison to a two-layer model. & 2017 & Medical Field & High Quality \\ \hline
[103] & In this study, the association between fractures and inhaled corticosteroids is investigated through the DSS. & 2018 & Medical Field & High Quality \\ \hline
[5] & A review of DSS was conducted for heart disease diagnosis in the clinical setting. The review considered the types of diseases, data set formation methods, usage of machine learning algorithms, types of comparators as well as the clinical implications for the reported decision support systems. & 2018 & Medical Field & High Quality \\ \hline
[43] & DSS for the prediction of a number of liver diseases such as alcoholic liver damage, liver cirrhosis, primary hepatoma, and cholelithiasis. & 2018 & Medical Field & High Quality \\ \hline
[44] & A review is provided regarding the applications and limitations of radiomics to develop better DSS for breast case diagnosis and prognosis. & 2018 & Medical Field & High Quality \\ \hline
[92] & The study presents a novel idea to implement the decision support system using the MEAN architecture and R statistical language platform. The proposed framework is verified by using the implementation of a user side, multi-participant decision support system supporting the group decision-making process, on the selection of the best as well as commonly agreed senior center for co-living after retirement. & 2019 & Medical Field & High Quality \\ \hline
[52] & The proposed study provides a medical DSS base on IoT and Soft computing to observe diabetes patients. & 2019 & Medical Field & High Quality \\ \hline
[45] & The study investigates the concordance of DSS and the recommendation of surgeons regarding back pain. & 2019 & Medical Field & High Quality \\ \hline
[47] & This study uses data from National Health Insurance Scheme claims, acquired from the hospitals in Ghana, for identifying health insurance fraud and other irregularities. Genetic support vector machines (GSVMs), which are new hybridized data mining and statistical machine learning tools are used. It offers a set of classy methods for the automatic discovery of fraudulent claims in health insurance databases. & 2019 & Medical Field & High Quality \\ \hline
[100] & The IDSS is embedded in system multi-agents to model the emergency process in operating rooms. A decision support system assists the agents to plan reflective surgery and in allocating human and necessary medical resources. & 2019 & Medical Field & High Quality \\ \hline
[48] & An overview of literature focused on investigating the currently available mDSS. The mDSS discussed is focused on prostate cancer (PCa). & 2019 & Medical Field & High Quality \\ \hline
[23] & The authors developed a procedure to identify the interventions for driving safety by taking information history of events happening on the road. A real case study is performed using the infrastructure of the road. & 2015 & Transportation & High Quality \\ \hline
[60] & In this paper, the authors describe the application of MCDA regarding the identification of routes for the vehicles which collect waste for recycling. & 2015 & Transportation & High Quality \\ \hline
[63] & MC-based DSS for devising the plan for shipments of hazardous material based on the geographical information. & 2015 & Transportation & High Quality \\ \hline \hline \end{tabular}
\end{table} 
Table 9: _Cont._Figure 11: Distribution of high-quality papers.