Artificial Intelligence: Definition and Background

Sheikh, Haroon; Prins, Corien; Schrijvers, Erik

doi:10.1007/978-3-031-21448-6_2

Cited by 46 publications

(24 citation statements)

References 7 publications

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“…Artificial intelligence (AI) has emerged to play an increasingly critical role in research, development, and testing within science, technology, engineering, and mathematics (STEM) and non-STEM disciplines (Xu et al, 2021). While there is no universally accepted definition of AI, it broadly refers to “systems that display intelligent behavior by analyzing their environment and taking actions—with some degree of autonomy—to achieve specific goals” (Sheikh et al, 2023, p. 20). AI has revolutionized a range of fields such as genomics (Dias & Torkamani, 2019; Quazi, 2022), education (Alqahtani et al, 2023), and drug and health-care research (Alowais et al, 2023; Chakraborty et al, 2023; Davenport & Kalakota, 2019).…”

Section: Implications For Practice and Researchmentioning

confidence: 99%

Leveraging Artificial Intelligence for Expediting Implementation Efforts

Younas,

Reynolds

2024

Creative Nursing

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Expedited implementation of evidence into practice and policymaking is critical to ensure the delivery of effective care and improve health-care outcomes. Implementation science deals with the designing of methods and strategies for increasing and facilitating the uptake of evidence into practice and policymaking. Nevertheless, the process of designing and selecting methods and strategies for implementing evidence is complicated because of the complexity of health-care settings where implementation is desired. Artificial intelligence (AI) has revolutionized a range of fields, including genomics, education, drug trials, research, and health care. This commentary discusses how AI can be leveraged to expedite implementation science efforts for transforming health-care practice. Four key aspects of AI use in implementation science are highlighted: (a) AI for implementation planning (e.g., needs assessment, predictive analytics, and data management), (b) AI for developing implementation tools and guidelines, (c) AI for designing and applying implementation strategies, and (d) AI for monitoring and evaluating implementation outcomes. Use of AI along the implementation continuum from planning to delivery and evaluation can enable more precise and accurate implementation of evidence into practice.

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Section: Implications For Practice and Researchmentioning

confidence: 99%

Leveraging Artificial Intelligence for Expediting Implementation Efforts

Younas,

Reynolds

2024

Creative Nursing

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“…Moreover, applications such as Watson, another AI application that IBM encountered with human intelligence, or AlphaGo of DeepMind by Google Inc. (US), which works with deep learning applications and can learn on, have shown the superiority of AI to humans in certain areas. 8,9 In analyzing the development of AI, a process of ups and downs, divided into periods with the names of seasons, is encountered that is as follows: "the beginning" in the 1950s, "the winter" between 1970 and 1980, "the spring" between 1990 and 2010, and "the summer" after 2010. 7,8…”

Section: History Of Aimentioning

confidence: 99%

“…8,9 In analyzing the development of AI, a process of ups and downs, divided into periods with the names of seasons, is encountered that is as follows: "the beginning" in the 1950s, "the winter" between 1970 and 1980, "the spring" between 1990 and 2010, and "the summer" after 2010. 7,8…”

Section: History Of Aimentioning

confidence: 99%

Understanding Artificial Intelligence and Applications in Oncology: Narrative Review

ÇİÇİN,

SAYIN

2024

J Oncol Sci

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ABS TRACT There is a rapid progression of information technologies in healthcare. One of the cornerstones of the process is AI, which uses a combination of multiple technologies in modern healthcare applications and has both administrative and clinical aspects. AI assists in the field of medicine by modifying the existing disease prevention procedures, diagnosis, treatment, drug development, clinical care, and other healthcare services; moreover, it is a promising modality in almost every field. In contrast, ethical issues such as accountability, personal data protection, patient safety, application bias, and trust issues are still debatable as they have not been fully addressed by AI. These discussions are based on the inadequacy of existing procedures, standards, and ethical rules for the ever-evolving AI technologies. Additionally, AI should be most intensively used for patients with oncologyand oncological applications. Thus, this article aimed to provide deep insights for a simple understanding of AI for oncologists.

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“…Artificial Intelligence (AI) is defined as the computations that are used for perceiving, reasoning, and acting [1]. In general, AI is also defined as the technology for enabling machines to imitate complex human skills [2]. The scientific goal of AI determines the ideas about knowledge representation, knowledge usage, and systems assembly for explaining various types of intelligence [1].…”

Section: Introductionmentioning

confidence: 99%

Use of Artificial Intelligence in Design, Development, Additive Manufacturing, and Certification of Multifunctional Composites for Aircraft, Drones, and Spacecraft

Ghimire,

Raji

2024

Applied Sciences

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Multifunctional composites provide more than one function from the same part. The anisotropy, material, and process characterization challenges and the lack of standardization on the 3D-printed multifunctional carbon composites make it difficult for application into aerospace. The current solutions for additive manufacturing (AM) technologies and additively manufactured monofunctional and multifunctional composites are not mature enough for safety-critical applications. A new approach is proposed to explore the use of machine learning (ML) in the design, development, AM, testing, and certification of multifunctional composites for aircraft, unmanned aircraft systems (UAS), and spacecraft. In this work, an artificial neural network (ANN) architecture is proposed. An AM-embedded building block approach integrates the complete lifecycle of aircraft, UAS, and spacecraft using ANN to support the continued operational safety (COS) of aircraft, spacecraft, and UAS. The proposed method exploits the power of ANN on the metadata for the characterization of multifunctional material properties and processes and the mapping of the failure modes compared with the predicted models and history. This paper provides an in-depth analysis and explanation of the new methods needed to overcome the existing barriers, problems, and situations.

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Artificial Intelligence: Definition and Background

Abstract: If we want to embed AI in society, we need to understand what it is. What do we mean by artificial intelligence? How has the technology developed? Where do we stand now?

Cited by 46 publications

References 7 publications

Leveraging Artificial Intelligence for Expediting Implementation Efforts

Leveraging Artificial Intelligence for Expediting Implementation Efforts

Understanding Artificial Intelligence and Applications in Oncology: Narrative Review

Use of Artificial Intelligence in Design, Development, Additive Manufacturing, and Certification of Multifunctional Composites for Aircraft, Drones, and Spacecraft

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