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Prompt Engineering in Medical Education

International Medical Education, 2023
Artificial intelligence-powered generative language models (GLMs), such as ChatGPT, Perplexity AI, and Google Bard, have the potential to provide personalized learning, unlimited practice opportunities, and interactive engagement 24/7, with immediate ...
Thomas F. Heston, Charya Khun
doaj   +3 more sources

Review of large vision models and visual prompt engineering

Meta-Radiology, 2023
Visual prompt engineering is a fundamental methodology in the field of visual and image artificial general intelligence. As the development of large vision models progresses, the importance of prompt engineering becomes increasingly evident.
Jiaqi Wang, Zhengliang Liu, Lin Zhao, Zihao Wu, Chong Ma, Sigang Yu, Haixing Dai, Qiushi Yang, Yiheng Liu, Songyao Zhang, Enze Shi, Yi Pan, Tuo Zhang, Dajiang Zhu, Xiang Li, Xi Jiang, Bao Ge, Yixuan Yuan, Dinggang Shen, Tianming Liu, Shu Zhang   +20 more
doaj   +3 more sources

Green prompt engineering for sustainable generative AI [PDF]

Environmental Science and Ecotechnology
Prompt engineering involves manual design and optimization of text-based instructions or queries, enabling precise control over outputs generated by pre-trained large language models (LLMs) and ensuring alignment with desired responses.
Sanjay Podder, Hema Date, Shankar Murthy
doaj   +2 more sources

Prompt Engineering

International Research Journal of Modernization in Engineering Technology & Science
<strong> Using intelligence to use artificial Intelligence: A deep dive into Prompt Engineering </strong> <strong> Author </strong> <strong> Dhruv Gupta (ORCID: </strong> <strong> 0009–0004–7109–5403 </strong> <strong> ) </strong> Introduction Large Language Models (LLMs) have become the new ...
Ajantha Devi Vairamani, Anand Nayyar
  +15 more sources

Prompt Engineering Paradigms for Medical Applications: Scoping Review

Journal of Medical Internet Research
BackgroundPrompt engineering, focusing on crafting effective prompts to large language models (LLMs), has garnered attention for its capabilities at harnessing the potential of LLMs. This is even more crucial in the medical domain
Jamil Zaghir, Marco Naguib, Mina Bjelogrlic, Aurélie Névéol, Xavier Tannier, Christian Lovis   +5 more
doaj   +3 more sources

Prompt Engineering in Clinical Practice: Tutorial for Clinicians [PDF]

Journal of Medical Internet Research
Large language models (LLMs), such as OpenAI’s GPT series and Google’s PaLM, are transforming health care by improving clinical decision-making, enhancing patient communication, and simplifying administrative tasks.
Jialin Liu, Fang Liu, Changyu Wang, Siru Liu   +3 more
doaj   +2 more sources

AI literacy and its implications for prompt engineering strategies

Computers and Education: Artificial Intelligence
Artificial intelligence technologies are rapidly advancing. As part of this development, large language models (LLMs) are increasingly being used when humans interact with systems based on artificial intelligence (AI), posing both new opportunities and ...
Nils Knoth, Antonia Tolzin, Andreas Janson, Jan Marco Leimeister   +3 more
doaj   +3 more sources

Prompt engineering as a new 21st century skill

Frontiers in Education
Artificial Intelligence (AI) promises to revolutionize nearly every aspect of human learning. However, users have observed that the efficacy of AI assistants hinges crucially on the quality of the prompts supplied to them.
Denis Federiakin, Dimitri Molerov, Olga Zlatkin-Troitschanskaia, Andreas Maur   +3 more
doaj   +3 more sources

Prompt engineering in higher education: a systematic review to help inform curricula

International Journal of Educational Technology in Higher Education
This paper presents a systematic review of the role of prompt engineering during interactions with Generative Artificial Intelligence (GenAI) in Higher Education (HE) to discover potential methods of improving educational outcomes.
Daniel Lee, Edward Palmer
doaj   +2 more sources

Prompting AI Art: An Investigation into the Creative Skill of Prompt Engineering

International Journal of Human-Computer Interaction
42 pages, 8 ...
Johanna Silvennoinen, Jonas Oppenlaender, Rhema Linder   +2 more
exaly   +5 more sources