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This study aimed to assess the potential of the Clinical Dementia Rating (CDR) Scale in the prognosis of dementia in elderly subjects.

Dementia staging severity is clinically an essential task, so the authors used machine learning (ML) on the magnetic resonance imaging (MRI) features to locate and study the impact of various MR readings onto the classification of demented and nondemented patients. The authors used cross-sectional MRI data in this study. The designed ML approach established the role of CDR in the prognosis of inflicted and normal patients. Moreover, the pattern analysis indicated CDR as a strong cohort amongst the various attributes, with CDR to have a significant value of p < 0.01. The authors employed 20 ML classifiers.

The mean prediction accuracy varied with the various ML classifier used, with the bagging classifier (random forest as a base estimator) achieving the highest (93.67%). A series of ML analyses demonstrated that the model including the CDR score had better prediction accuracy and other related performance metrics.

The results suggest that the CDR score, a simple clinical measure, can be used in real community settings. It can be used to predict dementia progression with ML modeling.

This paper aims to address three research questions (1) Who is the main stakeholder that shapes Airbnb experience, (2) Does Airbnb offers an authentic travel experience? and (3) What should be the future research trends in Airbnb?

This paper uses the systematic literature review (SLR) with a well-defined protocol, research strategy and methods to answer the research questions.

The review revealed that while Airbnb plays a significant role as the platform provider, the stakeholders influencing the experiences are multifaceted. Hosts, guests, local communities and even regulatory bodies all contribute to shaping the overall Airbnb Experience ecosystem. Hosts, in particular, have a crucial role in curating and delivering unique experiences, which significantly impacts the quality and authenticity of the offerings. On the question of whether Airbnb offers an authentic travel experience, the review uncovered mixed findings. For examples, some studies emphasized the potential for Airbnb to provide authentic and local experiences, allowing travelers to engage with the community and cultural aspects of a destination. However, other studies raised concerns about the commodification and standardization of experiences, leading to a potential loss of authenticity.

This paper is different from previous SLR where previous research systematically reviewed; motivations to use and choose Airbnb, institutionalization of Airbnb, stakeholders of Airbnb. This paper addresses authentic experience as a factor that influences activity participation.