Healthcare system: Moving forward with artificial intelligence

Dicuonzo, Grazia; Donofrio, Francesca; Fusco, Antonio; Shini, Matilda

doi:10.1016/j.technovation.2022.102510

Cited by 72 publications

(27 citation statements)

References 44 publications

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“…The evolution of digital healthcare into mobile healthcare (mobile health) has also made it possible to manage information via apps that a patient can download directly to their smartphone or tablet [ 89 ], allowing them to monitor their health status independently and share it with their doctor [ 44 , 90 ]. Therefore, IoT allows a much better and timely diagnosis of the patient’s status and offers medical services via telemedicine, even in remote locations [ 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 ] still underdeveloped, where the number of specialists in health services is insufficient [ 92 ]. The use of telemedicine is of fundamental importance in this SARS-CoV-2 pandemic period for preventing and managing COVID-19 infection [ 93 ].…”

Section: Resultsmentioning

confidence: 99%

“…To ensure a transparent and high-quality process, the analysis comprised four phases [ 68 ]: Planning and identification of studies Article evaluation Extraction of results Summary and dissemination of audit results …”

Section: Methodsmentioning

confidence: 99%

“…An additional degenerative disease in which to employ machine learning is Parkinson's disease, which affects the neurological system and limits mobility. For early detection of disease symptoms, some studies have used k-nearest neighbor, random forest, and decision tree algorithms [67,68]. Sivaparthipan et al (2019) also highlighted the importance of data collection using cell phones to recognize the gait of Parkinson's patients [69].…”

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confidence: 99%

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Towards the Use of Big Data in Healthcare: A Literature Review

et al. 2022

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The interest in new and more advanced technological solutions is paving the way for the diffusion of innovative and revolutionary applications in healthcare organizations. The application of an artificial intelligence system to medical research has the potential to move toward highly advanced e-Health. This analysis aims to explore the main areas of application of big data in healthcare, as well as the restructuring of the technological infrastructure and the integration of traditional data analytical tools and techniques with an elaborate computational technology that is able to enhance and extract useful information for decision-making. We conducted a literature review using the Scopus database over the period 2010–2020. The article selection process involved five steps: the planning and identification of studies, the evaluation of articles, the extraction of results, the summary, and the dissemination of the audit results. We included 93 documents. Our results suggest that effective and patient-centered care cannot disregard the acquisition, management, and analysis of a huge volume and variety of health data. In this way, an immediate and more effective diagnosis could be possible while maximizing healthcare resources. Deriving the benefits associated with digitization and technological innovation, however, requires the restructuring of traditional operational and strategic processes, and the acquisition of new skills.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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confidence: 99%

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Towards the Use of Big Data in Healthcare: A Literature Review

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“…For example, Arjun et al [6] addressed the current study of banking by providing a comprehensive review covering the period from 1970 to 2020 and focusing on intelligent decision support models in the banking industry. Çürük and Kaynar [18] investigated research on Islamic finance, Islamic banking, and Islamic economy, during the post-crisis period (2008-2020) using the Web of Science database; the author found that Malaysia was the most active country in terms of publications and citations.…”

Section: Of 11mentioning

confidence: 99%

Artificial Intelligence in the Islamic Finance: A bibliometric Analysis

Tayachi¹,

Brahimi²,

Essafi³

et al. 2022

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The paper demonstrates the future of artificial intelligence in the Islamic Banks of Saudi Arabia which introduces with the meaning of artificial intelligence and the benefits which AI may bring with itself in the future. Further, how banks differ in their use of AI from the banks that do not use AI or use original intelligence (Artificial Neural Network) and the acknowledgement of 4 purely Islamic banks in KSA. The literature has analyzed the pros of AI in the Islamic banks taking into consideration machine learning, natural language processing, text mining through neural network of deep learning, algorithmic trading and robotics. It has further analyzed AI’s limitations with regards to its costs, technological unemployment, lack of human creativity and its accountability and regulation. Lastly, the literature has stated AI from the sharia’a point of view. In order to test hypothesis concerning future studies, it was important to collect data using purely Islamic banks. Upon various interpretations concerning AI’s accountability and its impact on sharia’a board, robot’s impact in the long run, AI’s ethics and its uses which people have already encountered and the time period for which AI may imitate human learning in the future- we find that generation Z and millennials are very influenced by AI and have positive views about its scope in the future. However, it is important to note that research limitations include no access to banking authorities due to the recovery after the pandemic of COVID-19 besides.

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“…Artificial intelligence (AI) in healthcare is becoming increasingly essential due to its potential to enhance clinical risk predictions and advanced administration within the organization. Thus, implementing AI to achieve these desired benefits is expected in ED [ 6 ]. Therefore, focusing on practicalities, the ED in Chi Mei Medical Center (CMMC) has developed and implemented eight artificial intelligence (AI) disease predictive systems and integrated them into the HIS, including influenza in old age, chest pain, pancreatitis, hyperglycemic crisis, dengue, pneumonia, brain trauma, and fever.…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of a Comprehensive AI Dashboard for Real-Time Prediction of Adverse Prognosis of ED Patients

et al. 2022

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The emergency department (ED) is at the forefront of medical care, and the medical team needs to make outright judgments and treatment decisions under time constraints. Thus, knowing how to make personalized and precise predictions is a very challenging task. With the advancement of artificial intelligence (AI) technology, Chi Mei Medical Center (CMMC) adopted AI, the Internet of Things (IoT), and interaction technologies to establish diverse prognosis prediction models for eight diseases based on the ED electronic medical records of three branch hospitals. CMMC integrated these predictive models to form a digital AI dashboard, showing the risk status of all ED patients diagnosed with any of these eight diseases. This study first explored the methodology of CMMC’s AI development and proposed a four-tier AI dashboard architecture for ED implementation. The AI dashboard’s ease of use, usefulness, and acceptance was also strongly affirmed by the ED medical staff. The ED AI dashboard is an effective tool in the implementation of real-time risk monitoring of patients in the ED and could improve the quality of care as a part of best practice. Based on the results of this study, it is suggested that healthcare institutions thoughtfully consider tailoring their ED dashboard designs to adapt to their unique workflows and environments.

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Healthcare system: Moving forward with artificial intelligence

Cited by 72 publications

References 44 publications

Towards the Use of Big Data in Healthcare: A Literature Review

Towards the Use of Big Data in Healthcare: A Literature Review

Artificial Intelligence in the Islamic Finance: A bibliometric Analysis

Design and Implementation of a Comprehensive AI Dashboard for Real-Time Prediction of Adverse Prognosis of ED Patients

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