AI in Research
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The use of AI to advance scientific research, improve data analysis, and enable discoveries across disciplines, including the acceleration of drug discovery and climate modeling.
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Browsing AI in Research by Author "will be generated::orcid::0000-0003-3644-0553"
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Item Artificial Intelligence: The Game Changer in Scientific Research(2024-08-08) Ilegbusi, PaulArtificial Intelligence (AI) has revolutionised scientific research by enhancing data analysis, accelerating research processes, and improving accuracy. AI's applications span various fields, including biomedicine, environmental science, physics, and materials science. This paper explores AI's transformative impact on scientific research, highlighting its role, applications, challenges, and future prospects. AI tools, such as Explain Paper, Paper Digest, and Chatdoc, facilitate research by summarizing papers, explaining complex concepts, and assisting with literature reviews. Despite AI's benefits, challenges persist, including data privacy and security concerns, bias, and transparency issues. To address these challenges, the paper emphasizes the need for ethical guidelines, robust security measures, and interpretable AI models. The future of AI in scientific research holds promise, with emerging trends and technologies, interdisciplinary innovations, and collaborative platforms driving progress. The paper concludes by highlighting the importance of addressing AI's challenges to ensure its beneficial impact on science and society.Item The integration of Artificial intelligence (AI) in literature review and its potentials to revolutionize scientific knowledge acquisition(2024-04-28) Ilegbusi, PaulThis presentation discusses the role of artificial intelligence (AI) in enhancing the literature review process and its potential to transform scientific knowledge acquisition. The presentation highlights the importance of literature review in research and the challenges associated with the traditional manual approach. The presentation emphasizes that integrating AI in literature review can significantly improve efficiency, accuracy, and reduce bias. AI-powered tools can automate various aspects of the literature review process, including search, selection, analysis, and synthesis of relevant literature. The benefits of AI in literature review include increased efficiency, improved coverage of literature, and the ability to identify gaps in knowledge and uncover new research questions. The presentation also provides a comprehensive list of AI tools that can be used in literature review, such as Cramly.ai, Quillbot, GPT-minus 1, ChatGPT, Samwell.ai, and many others. These tools offer functionalities such as rewriting, paraphrasing, summarizing, understanding literature, and extracting key information from articles. The future of AI in literature review is promising, with emerging trends such as deep learning models and knowledge graphs. These trends have the potential to enhance the accuracy and comprehensiveness of literature reviews. In conclusion, the integration of AI in literature review has the potential to revolutionize scientific knowledge acquisition by improving efficiency, accuracy, and coverage of literature. By combining AI with human expertise, researchers can unlock new insights and accelerate scientific progress in various fields.