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Browsing by Author "Joshi, LR"

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    Use of Artificial Intelligence in Medical Research: A SWOT Analysis
    (Kathmandu University, 2024) Jha, JP; Amgain, K; Joshi, LR
    ABSTRACT As artificial intelligence (AI) tools are shaping our work, this article discusses a nuanced SWOT analysis, focusing on the applications of artificial intelligence in the area of medical research. It aims to evaluate the applications of artificial intelligence tools in medical research, discussing their implications for researchers, journals and the scientific community, addressing the growing concerns of using artificial intelligence tools in research and publication, evaluating its potential risks while harnessing the transformative potential. The analysis is complemented by a qualitative review of online resources, articles, blogs, interviews and podcasts, elucidating the prevailing themes in artificial intelligence-related considerations. The strengths highlight artificial intelligence’s capacity to accelerate research processes, particularly in diagnostics, drug production and data analysis. On the other hand, the weaknesses underscore concerns related to interpretability, biases, and ethical considerations, urging caution in artificial intelligence reliance. Opportunities arise in the form of explainable artificial intelligence, inclusive data practices, and enhanced model validation, while threats include issues of bias, privacy, overreliance and human exploitation. Such issues can be mitigated by collaboration from multiple experts and policymakers. The current state of artificial intelligence raises concerns about data quality, bias, transparency and ethical issues in its development and deployment. There is a need for collaborative efforts to establish ethical frameworks, regulations, and sustainability practices. A balanced approach, positioning AI as a collaborator that enhances human insights and creativity is recommended. KEY WORDS Artificial intelligence, Bias, Ethics, Medical research

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