Data Analytics in Smart Healthcare: The Recent Developments and Beyond

Abstract

The concepts of the smart city and the Internet of Things (IoT) have been facilitating the rollout of medical devices and systems to capture valuable information of humanity. A lot of artificial intelligence techniques have been demonstrated to be effective in smart city applications like energy, transportation, retail and control. In recent decade, retardation of the adoption of data analytics algorithms and systems in healthcare has been decreasing, and there is tremendous growth in data analytics research on healthcare data. The results of analytics aim at improving people's quality of life as well as relieving the issue of medical shortages. In this special issue "Data Analytics in Smart Healthcare", thirteen (13) papers have been published as the representative examples of recent developments. Guest Editors also highlight some emergent topics and opening challenges in healthcare analytics which follow the visions of the movement of healthcare analytics research.

Contributions and Risks of Artificial Intelligence (AI) in Building Smarter Cities: Insights from a Systematic Review of the Literature

“…In addition to health monitoring, AI systems can greatly improve health diagnosis by providing an effective repository of medical knowledge and the ability to access, analyze, and apply complex medical data more efficiently [68,139]. Assisting health care workers with tasks involving the collection and recording of data and knowledge could increase the amount of resources available for patient care [68,139], improve the quality of life for patients [120], and expand the professional learning capabilities of professionals [122]. Similarly, the improved analytics and reasoning capabilities of AI would provide a decision-support mechanism with the potential to reduce chances of misdiagnosis [137], facilitate greater communication and collaboration between health care professionals [70], and assist with the development of more personalized medical treatments [91,137].…”

Covid-19 sentiments in smart cities: The role of technology anxiety before and during the pandemic

“…Even before the pandemic, smart technologies contributed to redesign the configuration of urban spaces. However, despite the revolutionary role of technology in smart cities, it has been noticed that intelligent tools do not automatically allow the achievement of well-being and innovation ( Lytras and Visvizi, 2018 , Lytras et al, 2019a , Lytras et al, 2019b , Lytras et al, 2021 ). Adopting technology could be necessary but not a sufficient condition for the effective readaptation and redefinition of the organizational models imposed by the desire to overcome the health emergency.…”

“…Adopting technology could be necessary but not a sufficient condition for the effective readaptation and redefinition of the organizational models imposed by the desire to overcome the health emergency. Human interaction with technology is mediated by the political and institutional context in which the technologies are implemented ( Lytras and Visvizi, 2018 , Lytras et al, 2019a , Lytras et al, 2019b , Lytras et al, 2021 ). The most recent contributions in literature highlight the need to explore how humane smart cities can help manage critical issues in the administration of smart cities through entrepreneurship, governance, and citizens' inclusion ( Kitchin.…”

eGAP: An Evolutionary Game Theoretic Approach to Random Forest Pruning

“…In the quest to realise smart cities, a number of predictive smart healthcare applications were developed as outlined in [6]. A prediction of inpatient violence incidents was investigated in [10] using recurrent neural network, convolutional neural network, Naïve Bayes, support vector machine, and decision tree.…”

“…Consequently, many smart applications have come into existence in many areas including but not limited to smart energy [2], smart education [3], smart transportation [4], and smart healthcare [5]. For the latter area, which is the relevant one to the research conducted in this paper, many smart healthcare applications were developed as outlined in [6]. For such applications that are concerned with making predictions on new data based on historical data, it is imperative for such predictions to be as accurate as possible to reduce costs of treatment, avoid preventable diseases, predict outbreaks of epidemics, avoid preventable deaths, and improve the quality of life in general.…”