The Application of Artificial Intelligence Technology in Healthcare: A Systematic Review

Alloghani, Mohamed; Al‐Jumeily, Dhiya; Aljaaf, Ahmed J.; Khalaf, Mohammed; Mustafina, Jamila; Tan, Sin Ying

doi:10.1007/978-3-030-38752-5_20

Cited by 28 publications

(26 citation statements)

References 23 publications

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“…Let us consider the following scenario in the healthcare domain. The consumer is a newly established cancer treatment hospital, and the data sources are already established cancer treatment hospitals from different geographical locations across the globe 1 . The goal of the new hospital is to construct an ML model that can predict the early onset of a given form of cancer.…”

Section: Technical Aspects Of Ai Marketplacementioning

confidence: 99%

“…Therefore the developer should be able to assess the performance of model revisions on the validation dataset up to a relatively small fixed number of tests. The total number of validation tests should be small and fixed to 1 Recently, the European Commission adopted a recommendation on a European electronic health record exchange format. The recommendation supports the digital transformation of health and the flow of health data between hospitals within the EU [21].…”

Section: Technical Aspects Of Ai Marketplacementioning

confidence: 99%

“…Specifically, when widely diffused, AI models have the potential to solve many ubiquitous problems in domains ranging from healthcare to transportation. For example, neural network-based models have shown human and super-human level performance in many health-related diagnostic tasks such as breast cancer detection [1].…”

Section: Introductionmentioning

confidence: 99%

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Sketching an AI Marketplace: Tech, Economic, and Regulatory Aspects

et al. 2021

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Section: Technical Aspects Of Ai Marketplacementioning

confidence: 99%

Section: Technical Aspects Of Ai Marketplacementioning

confidence: 99%

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Sketching an AI Marketplace: Tech, Economic, and Regulatory Aspects

et al. 2021

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“…However, caregiver burden and patient fears of loss of independence remain high despite progress made [5,6]. The advent of personalised healthcare and wearable computing to track health could provide hope for overcoming these problems, with a system that could track and predict the difficulties of people with dementia and automatically intervene being feasible; personalised health systems already exist for other conditions [7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Review of Methods for Data Collection Experiments with People with Dementia and the Impact of COVID-19

Harper

Ghali

Hussain

et al. 2021

Intelligent Computing Theories and Application

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The development of a wearable-based system for detecting difficulties in the daily lives of people with dementia would be highly useful in the day-today management of the disease. To develop such a system, it would be necessary to identify physiological indicators of the difficulties, which can be identified by analyzing physiological datasets from people with dementia. However, there is no such data available to researchers. As such, it is vital that data is collected and made available in future. In this paper we perform a review of past physiological data collection experiments conducted with people with dementia and evaluate the methods used at each stage of the experiment. Consideration is also given to the impacts and limitations imposed by the COVID-19 pandemic and lockdowns both on the people with dementia-such people being one of the most at risk and affected groups-and on the efficacy and safety of each of the methods. It is concluded that the choice of method to be utilized in future data collection experiments is heavily dependent on the type and severity of the dementia the participants are experiencing, and that the choice of remote or COVID-secure methods should be used during the COVID-19 pandemic; many of the methods reviewed could allow for the spread of the virus if utilized during a pandemic.

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“…It was anticipated that 2020 is the beginning of an exciting decade in which we thought that we are mature enough to face global challenges such as infectious diseases, global warming, space invasion, and yet others. Undoubtedly, the development of basic science and technology frameworks toward data intensive applications has improved in vital healthcare areas including neuroscience, genomics, pharmaceutical development, medical imaging, and many others [1][2][3][4]. Eminent big technology innovations such as IoT technology [5], digital and mobile health [6], big data methods [7], along with the advances in artificial intelligence and machine learning can work toward smart solutions to deliver essential insights into global challenges such as COVID-19 pandemics via managing people with COVID-19 concerns and unlocking modern therapeutic solutions [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

An online COVID-19 self-assessment framework supported by IoMT technology

Khan

2021

Journal of Intelligent Systems

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As COVID-19 pandemic continued to propagate, millions of lives are currently at risk especially elderly, people with chronic conditions and pregnant women. Iraq is one of the countries affected by the COVID-19 pandemic. Currently, in Iraq, there is a need for a self-assessment tool to be available in hand for people with COVID-19 concerns. Such a tool would guide people, after an automated assessment, to the right decision such as seeking medical advice, self-isolate, or testing for COVID-19. This study proposes an online COVID-19 self-assessment tool supported by the internet of medical things (IoMT) technology as a means to fight this pandemic and mitigate the burden on our nation’s healthcare system. Advances in IoMT technology allow us to connect all medical tools, medical databases, and devices via the internet in one collaborative network, which conveys real-time data integration and analysis. Our IoMT framework-driven COVID-19 self-assessment tool will capture signs and symptoms through multiple probing questions, storing the data to our COVID-19 patient database, then analyze the data to determine whether a person needs to be tested for COVID-19 or other actions may require to be taken. Further to this, collected data can be integrated and analyzed collaboratively for developing a national health policy and help to manage healthcare resources more efficiently. The IoMT framework-driven online COVID-19 self-assessment tool has a big potential to prevent our healthcare system from being overwhelmed using real-time data collection, COVID-19 databases, analysis, and management of people with COVID-19 concerns, plus providing proper guidance and course of action.

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The Application of Artificial Intelligence Technology in Healthcare: A Systematic Review

Cited by 28 publications

References 23 publications

Sketching an AI Marketplace: Tech, Economic, and Regulatory Aspects

Sketching an AI Marketplace: Tech, Economic, and Regulatory Aspects

Review of Methods for Data Collection Experiments with People with Dementia and the Impact of COVID-19

An online COVID-19 self-assessment framework supported by IoMT technology

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