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User Preferences for AI-based Healthcare Apps: an Association Mining Analysis

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Abstract

This study investigated the factors influencing user preferences for AI-based healthcare apps. The study found that factors such as gender, real-time updates, ease of use, customization, cost, and privacy and security are all important considerations for users. The study also found that there are significant associations between different factors and the perceived importance of specific features and attributes of AI-based healthcare apps. For example, females are more likely to value privacy and security when considering real-time updates as extremely important. Additionally, users who prioritize usability, customization options, and real-time updates are more likely to perceive accurate recommendations as extremely important. The findings of this study emphasize the importance of considering factors such as gender, real-time updates, ease of use, customization, cost, and privacy and security when designing and developing AI-based healthcare apps. By understanding the preferences and factors influencing users’ decisions, developers can tailor their apps to better meet the needs and expectations of individuals, ultimately enhancing user satisfaction and engagement.

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Data Availability

The findings of this study, presented in the form of data, are accessible within the research study itself. Given that the analysis utilized survey data, it was explicitly communicated to all respondents before data collection that their information would be treated confidentially. As a result, additional data or detailed information beyond what is presented in the study cannot be disclosed. For any supplementary information, interested parties may contact the corresponding author.

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Authors

Contributions

All authors contributed significantly to the conception, design, data analysis, and interpretation of the findings. All authors have critically reviewed and approved the final manuscript for publication.

Corresponding author

Correspondence to Akanksha Upadhyaya.

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Conflict of Interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Research Involving Human and /or Animal

Human participants aged 18–60 years were involved in this research on a voluntary basis. Prior to their participation, respondents were explicitly assured that any information they provided would be treated with confidentiality.

Informed Consent

Participants were explicitly guaranteed that the information they shared would be handled confidentially. The data utilized underwent anonymization and aggregation processes to uphold privacy standards and ethical considerations. The study abstains from including any personal identifiers, ensuring that subjects' privacy is safeguarded. Importantly, the research carries no potential harm or risk to the participants.

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This article is part of the topical collection “AI Based Internet of Healthcare: Analysis and Future Perspectives” guest edited by Diganta Sengupta, Debashis De and Prasenjit Bhadra.

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Upadhyaya, A., Mishra, M.K. & Saxena, A. User Preferences for AI-based Healthcare Apps: an Association Mining Analysis. SN COMPUT. SCI. 5, 464 (2024). https://doi.org/10.1007/s42979-024-02739-y

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