INTRODUCTION: Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting outcome in many clinical scenarios. METHODS: Medline and internet searches were carried out using the keywords 'artificial intelligence' and 'neural networks (computer)'. Further references were obtained by cross-referencing from key articles. An overview of different artificial intelligent techniques is presented in this paper along with the review of important clinical applications. RESULTS: The proficiency of artificial intelligent techniques has been explored in almost every field of medicine. Artificial neural network was the most commonly used analytical tool whilst other artificial intelligent techniques such as fuzzy expert systems, evolutionary computation and hybrid intelligent systems have all been used in different clinical settings. DISCUSSION: Artificial intelligence techniques have the potential to be applied in almost every field of medicine. There is need for further clinical trials which are appropriately designed before these emergent techniques find application in the real clinical setting.

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Artificial intelligence in medicine.

In recent years there has been increasing interest in transport and sustainability studies. However, there has been no formal definition on the concept of sustainable transport. In this paper, we attempt to formalise the concept in a framework of dynamic welfare analysis. Using a control-theoretic model, we characterise a sustainable transport as the development of the transport sector that can support a maximum sustainable social welfare measured by an augmented net national product with environmental values taken into account. Dynamic interactions between transport, production, consumption and technological changes are also discussed. For the covering abstract and the URL of the conference see ITRD E205769. (A)

What is sustainable transport

Study on artificial intelligence: The state of the art and future prospects

Artificial intelligence (AI) is one of the most disruptive technologies of our time. Interest in the use of AI for urban innovation continues to grow. Particularly, the rise of smart cities—urban locations that are enabled by community, technology, and policy to deliver productivity, innovation, livability, wellbeing, sustainability, accessibility, good governance, and good planning—has increased the demand for AI-enabled innovations. There is, nevertheless, no scholarly work that provides a comprehensive review on the topic. This paper generates insights into how AI can contribute to the development of smarter cities. A systematic review of the literature is selected as the methodologic approach. Results are categorized under the main smart city development dimensions, i.e., economy, society, environment, and governance. The findings of the systematic review containing 93 articles disclose that: (a) AI in the context of smart cities is an emerging field of research and practice. (b) The central focus of the literature is on AI technologies, algorithms, and their current and prospective applications. (c) AI applications in the context of smart cities mainly concentrate on business efficiency, data analytics, education, energy, environmental sustainability, health, land use, security, transport, and urban management areas. (d) There is limited scholarly research investigating the risks of wider AI utilization. (e) Upcoming disruptions of AI in cities and societies have not been adequately examined. Current and potential contributions of AI to the development of smarter cities are outlined in this paper to inform scholars of prospective areas for further research.

https://www.mdpi.com/1996-1073/13/6/1473/pdf

Contributions and risks of artificial intelligence (AI) in building smarter cities: Insights from a systematic review of the literature

Culture, in its various forms, has always been a critical driver of innovation This paper focuses on generating some insights into the role of “culture for open innovation dynamics” First, because the requirement to understand culture, which can control open innovation complexity, has been augmented, we want to answer the following research question in this study: How can we define or organize “culture for open innovation dynamics”, which can motivate open innovation dynamics, and control open innovation complexity? Second, we propose a concept model of culture for open innovation dynamics by reviewing the literature on the culture of firms in terms of their traits, organization, static innovation, and dynamic aspects regarding their innovation in entrepreneurship, and we validate said model through an indirect social experiment using the research results of 23 Special Issue papers Third, the concept model of culture for open innovation dynamics is explained as the interaction between three different entrepreneurship dimensions: Entrepreneurship of novice entrepreneurs, intrapreneurship of employees of an existing firm, and organizational entrepreneurship by the firm itself According to the balance of three sub-entrepreneurship types, culture for open innovation dynamics can have different aspects, namely, entrepreneurship leading culture for open innovation dynamics, intrapreneurship leading culture for open innovation dynamics, or organizational entrepreneurship leading culture for open innovation dynamics This paper helps organizations and entrepreneurs to better understand the role that culture plays in boosting open innovation dynamics

The Culture for Open Innovation Dynamics

In recent years, artificial intelligence (AI) has started to manifest itself at an unprecedented pace. With highly sophisticated capabilities, AI has the potential to dramatically change our cities and societies. Despite its growing importance, the urban and social implications of AI are still an understudied area. In order to contribute to the ongoing efforts to address this research gap, this paper introduces the notion of an artificially intelligent city as the potential successor of the popular smart city brand—where the smartness of a city has come to be strongly associated with the use of viable technological solutions, including AI. The study explores whether building artificially intelligent cities can safeguard humanity from natural disasters, pandemics, and other catastrophes. All of the statements in this viewpoint are based on a thorough review of the current status of AI literature, research, developments, trends, and applications. This paper generates insights and identifies prospective research questions by charting the evolution of AI and the potential impacts of the systematic adoption of AI in cities and societies. The generated insights inform urban policymakers, managers, and planners on how to ensure the correct uptake of AI in our cities, and the identified critical questions offer scholars directions for prospective research and development.

Can Building "Artificially Intelligent Cities" Safeguard Humanity from Natural Disasters, Pandemics, and Other Catastrophes? An Urban Scholar's Perspective.

Barriers and risks of Mobility-as-a-Service (MaaS) adoption in cities: A systematic review of the literature

Recent smart urban mobility innovations such as intelligent transportation systems, electric vehicles, autonomous vehicles, demand-responsive transportation, shared transportation, and mobility-as-a-service are consistently identified as the panacea to many of the economic, social and environmental effects associated with private vehicles—including road congestion, urban sprawl, social exclusion, increased costs, crashes, emissions, and environmental degradation. One of the strategies of many smart urban mobility policies is to view the transportation system from a holistic perspective to seek reduction of negative effects and an improve performance. Nonetheless, given the rapid technological advances in the transportation sector, there is a need to identify and evaluate primary smart mobility innovations from a sustainability perspective. This article presents a thorough technology review and evaluation of the main smart mobility innovations identified in the literature. The study has identified and categorized six main smart mobility innovations most commonly discussed within the literature including: (a) intelligent transport systems; (b) alternative fuel systems; (c) driving automation systems; (d) shared mobility services; (e) demand responsive transport; and (f) integrated mobility systems. Furthermore, this article includes a brief description of their characteristics, applications, and also evaluates their sustainability according to their proposed impacts on transport safety, road congestion, energy consumption, the environment, and accessibility.

/pdf/smart-urban-mobility-innovations-a-comprehensive-review-and-hen88gcqc1.pdf

Smart Urban Mobility Innovations: A Comprehensive Review and Evaluation

Transportation disadvantage is about the difficulty accessing mobility services required to complete activities associated with employment, shopping, business, essential needs, and recreation. Technological innovations in the field of smart mobility have been identified as a potential solution to help individuals overcome issues associated with transportation disadvantage. This paper aims to provide a consolidated understanding on how smart mobility innovations can contribute to alleviate transportation disadvantage. A systematic literature review is completed, and a conceptual framework is developed to provide the required information to address transportation disadvantage. The results are categorized under the physical, economic, spatial, temporal, psychological, information, and institutional dimensions of transportation disadvantage. The study findings reveal that: (a) Primary smart mobility innovations identified in the literature are demand responsive transportation, shared transportation, intelligent transportation systems, electric mobility, autonomous vehicles, and Mobility-as-a-Services. (b) Smart mobility innovations could benefit urban areas by improving accessibility, efficiency, coverage, flexibility, safety, and the overall integration of the transportation system. (c) Smart mobility innovations have the potential to contribute to the alleviation of transportation disadvantage. (d) Mobility-as-a-Service has high potential to alleviate transportation disadvantage primarily due to its ability to integrate a wide-range of services.

Luke Butler

Papers

Contributions and risks of artificial intelligence (AI) in building smarter cities: Insights from a systematic review of the literature

Can Building "Artificially Intelligent Cities" Safeguard Humanity from Natural Disasters, Pandemics, and Other Catastrophes? An Urban Scholar's Perspective.

Barriers and risks of Mobility-as-a-Service (MaaS) adoption in cities: A systematic review of the literature

Smart Urban Mobility Innovations: A Comprehensive Review and Evaluation

How Can Smart Mobility Innovations Alleviate Transportation Disadvantage? Assembling a Conceptual Framework through a Systematic Review