Towards an Application Helping to Minimize Medication Error Rate

Alharbi, Ali I.; AlGhamdi, Mohammed J.; Alturki, Ryan; Alyamani, Hasan J.

doi:10.1155/2021/9221005

Cited by 6 publications

(2 citation statements)

References 37 publications

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“…The recent exponential advancement in technology has ushered in a new era of artificial intelligence- (AI-) enabled mobile applications (apps) that are used globally by people from all walks of life. AI is increasingly becoming a significant part of people's everyday lives [ 1 , 2 ]. The global adoption of smartphones and tablets has led to widespread use of AI in mobile applications ranging from healthcare systems to finance to entertainment [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

Towards Understanding the Usability Attributes of AI-Enabled eHealth Mobile Applications

Alzahrani

Gay

Alturki

et al. 2021

Journal of Healthcare Engineering

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Mobile application (app) use is increasingly becoming an essential part of our daily lives. Due to their significant usefulness, people rely on them to perform multiple tasks seamlessly in almost all aspects of everyday life. Similarly, there has been immense progress in artificial intelligence (AI) technology, especially deep learning, computer vision, natural language processing, and robotics. These technologies are now actively being implemented in smartphone apps and healthcare, providing multiple healthcare services. However, several factors affect the usefulness of mobile healthcare apps, and usability is an important one. There are various healthcare apps developed for each specific task, and the success of these apps depends on their performance. This study presents a systematic review of the existing apps and discusses their usability attributes. It highlights the usability models, outlines, and guidelines proposed in previous research for designing apps with improved usability characteristics. Thirty-nine research articles were reviewed and examined to identify the usability attributes, framework, and app design conducted. The results showed that satisfaction, efficiency, and learnability are the most important usability attributes to consider when designing eHealth mobile apps. Surprisingly, other significant attributes for healthcare apps, such as privacy and security, were not among the most indicated attributes in the studies.

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Section: Introductionmentioning

confidence: 99%

Towards Understanding the Usability Attributes of AI-Enabled eHealth Mobile Applications

Alzahrani

Gay

Alturki

et al. 2021

Journal of Healthcare Engineering

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“…Collaboration guidance may be enough to achieve competent nursing services. Also, there is an urgent demand for good communication about anticipated decisions in relation to therapeutic interventions between mentally ill elderly patients and nursing staff; this is a critical component of rehabilitation [36][37][38][39][40][41][42].…”

Section: Discussionmentioning

confidence: 99%

Advancing Sustainable Healthcare through Enhanced Therapeutic Communication with Elderly Patients in the Kingdom of Saudi Arabia

Alhakami,

Alsubait,

Alhakami

et al. 2023

Sustainability

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Effective communication in nursing, particularly with older patients, is critical to providing high-quality care. The purpose of this research is to fill key gaps in the existing literature by emphasizing the importance of therapeutic communication in the setting of mental nursing care for elderly patients in Saudi Arabia. Building on the study’s foundation, which recognizes the various issues faced by cultural, religious, and linguistic diversity, this research adopted a rigorous research methodology incorporating a broad group of senior healthcare professionals as experts. We analyze various therapeutic communication approaches used by mental health nurses using extensive surveys and observations. This empirical study’s findings are likely to make a significant addition to the field by throwing light on the most efficient methods for improving nurse–elderly-patient communication. The study identifies Simulation-Based Training as the most viable technique, with potentially far-reaching implications for improving care for older patients in Saudi Arabia. This study paves the way for significant advances in healthcare practices, with a focus on mental health nursing, ultimately helping both nurses and elderly patients by developing trust, understanding, and increased communication.

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Evaluation of machine learning-based regression techniques for prediction of diabetes levels fluctuations

Alkalifah,

Shaheen,

Alotibi

et al. 2025

Heliyon

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Towards an Application Helping to Minimize Medication Error Rate

Cited by 6 publications

References 37 publications

Towards Understanding the Usability Attributes of AI-Enabled eHealth Mobile Applications

Towards Understanding the Usability Attributes of AI-Enabled eHealth Mobile Applications

Advancing Sustainable Healthcare through Enhanced Therapeutic Communication with Elderly Patients in the Kingdom of Saudi Arabia

Evaluation of machine learning-based regression techniques for prediction of diabetes levels fluctuations

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