eHealth and Artificial Intelligence

Impedovo, Donato; Pirlo, Giuseppe

doi:10.3390/info10030117

Cited by 8 publications

(7 citation statements)

References 32 publications

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“…AI-based healthcare apps are a great way to help with health management. Many aspects of healthcare are being transformed by AI, including diagnostics, medication, and follow-ups [ 56 ]. AI and machine learning are expected to play significant roles in developing mHealth apps, perform additional general practitioner (GP) duties, and exhibit a greater number of their characteristics [ 57 ].…”

Section: Resultsmentioning

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: Resultsmentioning

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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show abstract

“…For example, to understand the phenotypic response and to recommend an optimal pharmacological dosage with sufficient safety and accuracy, only 3-6 data pairs may be necessary [ 51 , 52 ]. Artificial intelligence could prove crucial in managing and extracting relevant features from the multidimensional, noisy, and incomplete data as well as in following up with a variety of appropriate adaptations and actions [ 53 , 54 ]. It will be required to find the right balance of complexity and size of the data model versus the quality and rapid generation of actionable insights, according to the general premise of efficient use of artificial intelligence in health care [ 55 ].…”

Section: Omnichannel Engagement For Dhi-led Behavioral Changementioning

confidence: 99%

Omnichannel Communication to Boost Patient Engagement and Behavioral Change With Digital Health Interventions

Blasiak¹,

Sapanel²,

Leitman³

et al. 2022

J Med Internet Res

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Digital health interventions are being increasingly incorporated into health care workflows to improve the efficiency of patient care. In turn, sustained patient engagement with digital health interventions can maximize their benefits toward health care outcomes. In this viewpoint, we outline a dynamic patient engagement by using various communication channels and the potential use of omnichannel engagement to integrate these channels. We conceptualize a novel patient care journey where multiple web-based and offline communication channels are integrated through a “digital twin.” The principles of implementing omnichannel engagement for digital health interventions and digital twins are also broadly covered. Omnichannel engagement in digital health interventions implies a flexibility for personalization, which can enhance and sustain patient engagement with digital health interventions, and ultimately, patient quality of care and outcomes. We believe that the novel concept of omnichannel engagement in health care can be greatly beneficial to patients and the system once it is successfully realized to its full potential.

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“…The potential of using artificial intelligence in healthcare services is already undeniable. Numerous studies have already documented the suc-cessful implementation of AI in different areas of healthcare, whether it is health administration (Amato et al, 2019;Anderson & Agarwal, 2011;Diamond, Mostashari & Shirky, 2009;Dimitrov, 2016;Impedovo & Pirlo, 2019;Winter & Davidson, 2019;etc. ), diagnosis, prediction and decision support for physicians (Anakal & Sandhya, 2017;Arsene, Dumitrache & Mihu, 2015;Esteva et al, 2017;Lynn, 2019;Meena et al, 2019;Samuel, Omisore & Ojokoh, 2013;Seo, 2019;etc.…”

Section: Healthcare Services and Artificial Intelligencementioning

confidence: 99%

Implementation and Application of Artificial Intelligence in Selected Public Services

et al. 2021

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Data-intensive technologies, such as artificial intelligence, imply huge opportunities for transforming the delivery of healthcare and social services, improving people’s quality of life and working in the health and welfare system. The aim of this paper is to present examples of the implementation of artificial intelligence techniques in healthcare and social services and to sketch the trends and challenges in the adoption of artificial intelligence techniques, with an emphasis on the public sector and selected public services. Analysis is based on a realistic assessment of current artificial intelligence technologies and their anticipated development. Besides the benefits and potential opportunities for healthcare and social services, there are also challenges for governments. Understanding the huge potential of artificial intelligence as well as its limitations will be a key step forward, but it is essential to avoid the trap of an overestimation of artificial intelligence potential.

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eHealth and Artificial Intelligence

Cited by 8 publications

References 32 publications

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

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

Omnichannel Communication to Boost Patient Engagement and Behavioral Change With Digital Health Interventions

Implementation and Application of Artificial Intelligence in Selected Public Services

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