Alapfogalmak
Prompt engineering is a critical technique in natural language processing, especially in the healthcare domain, enabling models to perform specific tasks efficiently.
Kivonat
The content discusses the significance of prompt engineering in healthcare, focusing on methodologies and applications. It covers the development of prompt engineering, its applications in various medical tasks, and the challenges and future directions in this field. The review outlines the scope, basics, types of prompts (manual and automated), and their applications in classification, generation, detection, augmentation, question-answering, and inference tasks. It also highlights the importance of prompt design for improving model capabilities across different medical problems.
I. Introduction
Prompt engineering is crucial for enhancing performance in NLP tasks.
Recent advancements have shown significant potential for prompt-based methods.
Lack of comprehensive reviews specifically focusing on prompt engineering in healthcare.
II. Basic Knowledge
Large Language Models (LLMs) play a vital role in prompt design.
Elements and formats of prompts include cloze prompts and prefix prompts.
III. Types of Prompts
Manual Prompts:
Zero-shot prompting shows promise for various NLP tasks.
Automated Prompts:
Discrete prompting involves automatic search for templates.
IV. Applications of Prompts
Classification Task:
Medical image analysis using GPT4MIA shows strong performance.
Generation Task:
NapSS simplifies medical text using a multi-stage strategy.
Detection Task:
DeID-GPT effectively de-identifies private information from medical texts.
Augmentation Task:
ChatAug rephrases sentences to augment training data efficiently.
V. Challenges and Future Directions
Continuous improvement needed in techniques for model adaptation and domain-specific evaluation.
Statisztikák
Prompt engineeringは自然言語処理において重要であり、特に医療分野でモデルが特定のタスクを効率的に実行することを可能にします。