SACM - United States of America
Permanent URI for this collectionhttps://drepo.sdl.edu.sa/handle/20.500.14154/9668
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Item Restricted An In-Depth Analysis of the Adoption of Large Language Models in Clinical Settings: A Fuzzy Multi-Criteria Decision-Making Approach(University of Bridgeport, 2024-08-05) Aldwean, Abdullah; Tenney, DanThe growing capabilities of large language models (LLMs) in the medical field hold promising transformational change. The evolution of LLMs, such as BioBERT and MedGPT, has created new opportunities for enhancing the quality of healthcare services, improving clinical operational efficiency, and addressing numerous existing healthcare challenges. However, the adoption of these innovative technologies into clinical settings is a complex, multifaceted decision problem influenced by various factors. This dissertation aims to identify and rank the challenges facing the integration of LLMs into healthcare clinical settings and evaluate different adoption solutions. To achieve this goal, a combined approach based on the Fuzzy Analytic Hierarchy Process (FAHP) and the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) has been employed to prioritize these challenges and then use them to rank potential LLM adoption solutions based on experts’ opinion. However, utilizing LLMs technologies in clinical settings faces several challenges across societal, technological, organizational, regulatory, and economic (STORE) perspectives. The findings indicate that regulatory concerns, such as accountability and compliance, are considered the most critical challenges facing LLMs adoption decision. This research provides a thorough and evidence-based assessment of LLMs in the clinical settings. It offers a structured framework that helps decision-makers navigate the complexities of leveraging such disruptive innovations in clinical practice.34 0Item Restricted Fintech and Entrepreneurship: An Assessment Model to Evaluate Policy Instruments for Fintech Adoption by Small and Medium Enterprises (SMEs)(ProQuest, 2023-11-01) Alassaf, Deemah; Daim, Tugrul U.Small and medium enterprises (SMEs) are the engines that drive economic development. They are the backbone of the middle class as they provide social stability, innovation, inclusive growth, and poverty alleviation. SMEs contribute significantly to job creation, employment, tax provision and the Gross Domestic Product (GDP). However, they face inferior conditions and challenges when it comes to their financing compared to that of large enterprises, as well as having a high expectancy of failing. Because of these limitations, SMEs tend to grow slowly since building up higher credit is difficult for them, and in addition to this, they lack access to broad financing channels. Hence, Fintech solutions offer promising potential for improving SMEs’ access to finance through extending them more accessible and available services, more efficient credit risk assessments and reduced transaction costs. These tools can offer a valuable opportunity for ventures that are too small in size, and involve a great deal of risk, or serve a social purpose. While researchers and practitioners have been promoting Fintech as a potential financial safeguard for SMEs’ needs, evidence shows an inadequate adoption rate of SMEs to such solutions. Therefore, this research aims to provide a comprehensive examination for Fintech policy instruments and analyze their effectiveness on increasing the adoption of Fintech by SMEs through evaluating the essential policy targets impacting the adoption of Fintech and assessing their weights and priorities in the context of SMEs. The research was built upon an inclusive hierarchical decision model and a comprehensive literature review. Experts’ insights were utilized to identify the most important factors influencing Fintech adoption and policy effectiveness. The Hierarchical Decision Modeling (HDM) methodology was used to identify the relative importance of those factors proposing a policy evaluation tool to assess the effectiveness of policy instruments on increasing Fintech adoption. To test the practicality and value the research model adds to the research objective, a case study of the policy instrument effectiveness, the Saudi Arabian regulatory sandbox, was conducted. This research presents the identification of seventeen distinct policy targets that fall within four main perspectives along with their relative weights, as it also integrates the desirability curves methodology that measures the importance of each perspective and criterion. The case study was introduced to illustrate how the model could be used to identify the policy instrument’s actual performance in terms of influencing SMEs adoption of Fintech, identify the instrument’s strengths and weaknesses, and offer recommendations and guiding principles on how to improve the detected weaknesses to increase the policy instrument’s effectiveness on increasing the adoption of Fintech by SMEs.29 0