mlsanityData to 14 Oct 2026

Prompt Engineering for Healthcare: Methodologies and Applications

arXiv 2304.14670 ↗First posted 28 Apr 2023cs.AIcited by 52

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Abstract (arXiv)

Prompt engineering is a critical technique in the field of natural language processing that involves designing and optimizing the prompts used to input information into models, aiming to enhance their performance on specific tasks. With the recent advancements in large language models, prompt engineering has shown significant superiority across various domains and has become increasingly important in the healthcare domain. However, there is a lack of comprehensive reviews specifically focusing on prompt engineering in the medical field. This review will introduce the latest advances in prompt engineering in the field of natural language processing for the medical field. First, we will provide the development of prompt engineering and emphasize its significant contributions to healthcare natural language processing applications such as question-answering systems, text summarization, and machine translation. With the continuous improvement of general large language models, the importance of prompt engineering in the healthcare domain is becoming increasingly prominent. The aim of this article is to provide useful resources and bridges for healthcare natural language processing researchers to better explore the application of prompt engineering in this field. We hope that this review can provide new ideas and inspire for research and application in medical natural language processing.

Key facts. Cited by 52 papers in the map (data through 14 Oct 2026). Builds on 104 of its 144 references that are in the map. First posted on arXiv 28 Apr 2023.

Builds on

104 of 144 references.

References · 104

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2020Language Models are Few-Shot Learnerscited by 32,419
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  4. 2021Masked Autoencoders Are Scalable Vision Learnerscited by 7,403
  5. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,708
  6. 2021Prefix-Tuning: Optimizing Continuous Prompts for Generationcited by 3,915
  7. 2021The Power of Scale for Parameter-Efficient Prompt Tuningcited by 3,795
  8. 2022Prompt-to-Prompt Image Editing with Cross Attention Controlcited by 2,431
  9. 2021Learning to Prompt for Vision-Language Modelscited by 2,281
  10. 2021Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processingcited by 2,234
  11. 2019Language Models as Knowledge Bases?cited by 1,936
  12. 2022Large Language Models Encode Clinical Knowledgecited by 1,830
38 more
  1. 2020Making Pre-trained Language Models Better Few-shot Learnerscited by 1,256
  2. 2022Large Language Models Are Human-Level Prompt Engineerscited by 1,045
  3. 2022Ignore Previous Prompt: Attack Techniques For Language Modelscited by 832
  4. 2019Universal Adversarial Triggers for Attacking and Analyzing NLPcited by 722
  5. 2022PAL: Program-aided Language Modelscited by 652
  6. 2023Capabilities of GPT-4 on Medical Challenge Problemscited by 638
  7. 2023A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPTcited by 619
  8. 2021DenseCLIP: Language-Guided Dense Prediction with Context-Aware Promptingcited by 532
  9. 2020Pre-trained Models for Natural Language Processing: A Surveycited by 505
  10. 2018Generating Wikipedia by Summarizing Long Sequencescited by 335
  11. 2023ChatIE: Zero-Shot Information Extraction via Chatting with ChatGPTcited by 250
  12. 2020AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Promptscited by 249
  13. 2021Design Guidelines for Prompt Engineering Text-to-Image Generative Modelscited by 218
  14. 2018An Introduction to Deep Reinforcement Learningcited by 206
  15. 2023ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large Language Models in Multilingual Learningcited by 206
  16. 2022Can large language models reason about medical questions?cited by 194
  17. 2021Noisy Channel Language Model Prompting for Few-Shot Text Classificationcited by 165
  18. 2023Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Modelscited by 154
  19. 2021Template-Based Named Entity Recognition Using BARTcited by 153
  20. 2018Lessons from Natural Language Inference in the Clinical Domaincited by 151
  21. 2021OpenPrompt: An Open-source Framework for Prompt-learningcited by 148
  22. 2023DeID-GPT: Zero-shot Medical Text De-Identification by GPT-4cited by 130
  23. 2021Interpretable Deep Learning: Interpretation, Interpretability, Trustworthiness, and Beyondcited by 118
  24. 2023ChatCAD: Interactive Computer-Aided Diagnosis on Medical Image using Large Language Modelscited by 116
  25. 2022An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labelscited by 89
  26. 2022Adapting Pretrained Vision-Language Foundational Models to Medical Imaging Domainscited by 86
  27. 2021Can Language Models be Biomedical Knowledge Bases?cited by 83
  28. 2022Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methodscited by 79
  29. 2020The Radicalization Risks of GPT-3 and Advanced Neural Language Modelscited by 76
  30. 2023Can large language models build causal graphs?cited by 73
  31. 2022HyperPrompt: Prompt-based Task-Conditioning of Transformerscited by 67
  32. 2022Medical Image Understanding with Pretrained Vision Language Models: A Comprehensive Studycited by 66
  33. 2023Evaluating GPT-4 and ChatGPT on Japanese Medical Licensing Examinationscited by 63
  34. 2023Open-Ended Medical Visual Question Answering Through Prefix Tuning of Language Modelscited by 58
  35. 2023An Iterative Optimizing Framework for Radiology Report Summarization with ChatGPTcited by 57
  36. 2023Evaluation of ChatGPT for NLP-based Mental Health Applicationscited by 53
  37. 2022Dual Modality Prompt Tuning for Vision-Language Pre-Trained Modelcited by 52
  38. 2023See, Think, Confirm: Interactive Prompting Between Vision and Language Models for Knowledge-based Visual Reasoningcited by 51

50 most cited of 104 All 104 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 20; 2024: 19; 2025: 8; 2026: 5.

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  1. 2023Adapted Large Language Models Can Outperform Medical Experts in Clinical Text Summarizationcited by 246
  2. 2023Large Language Models for Generative Information Extraction: A Surveycited by 185
  3. 2023Rephrase and Respond: Let Large Language Models Ask Better Questions for Themselvescited by 123
  4. 2024Next-Generation Database Interfaces: A Survey of LLM-based Text-to-SQLcited by 120
  5. 2024Large Language Models for Robotics: Opportunities, Challenges, and Perspectivescited by 89
  6. 2023Diagnostic Reasoning Prompts Reveal the Potential for Large Language Model Interpretability in Medicinecited by 83
  7. 2023Review of Large Vision Models and Visual Prompt Engineeringcited by 77
  8. 2024Foundation Model for Advancing Healthcare: Challenges, Opportunities, and Future Directionscited by 77
  9. 2024Understanding LLMs: A Comprehensive Overview from Training to Inferencecited by 59
  10. 2023DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineercited by 57
  11. 2023SAMAug: Point Prompt Augmentation for Segment Anything Modelcited by 38
  12. 2023Psy-LLM: Scaling up Global Mental Health Psychological Services with AI-based Large Language Modelscited by 36
38 more
  1. 2023Artificial General Intelligence for Medical Imaging Analysiscited by 32
  2. 2023Exploring New Frontiers in Agricultural NLP: Investigating the Potential of Large Language Models for Food Applicationscited by 21
  3. 2024Position: Leverage Foundational Models for Black-Box Optimizationcited by 21
  4. 2023An Empirical Evaluation of Prompting Strategies for Large Language Models in Zero-Shot Clinical Natural Language Processingcited by 19
  5. 2023Holistic Evaluation of GPT-4V for Biomedical Imagingcited by 19
  6. 2024VisionGPT: LLM-Assisted Real-Time Anomaly Detection for Safe Visual Navigationcited by 14
  7. 2023Evaluating Large Language Models for Radiology Natural Language Processingcited by 12
  8. 2024GP-GPT: Large Language Model for Gene-Phenotype Mappingcited by 11
  9. 2023CliniDigest: A Case Study in Large Language Model Based Large-Scale Summarization of Clinical Trial Descriptionscited by 10
  10. 2023Ophtha-LLaMA2: A Large Language Model for Ophthalmologycited by 9
  11. 2024From Intention To Implementation: Automating Biomedical Research via LLMscited by 7
  12. 2025An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniquescited by 7
  13. 2024GPT-4 as Evaluator: Evaluating Large Language Models on Pest Management in Agriculturecited by 6
  14. 2024Improving LLM Group Fairness on Tabular Data via In-Context Learningcited by 6
  15. 2023ChatGPT-HealthPrompt. Harnessing the Power of XAI in Prompt-Based Healthcare Decision Support using ChatGPTcited by 5
  16. 2024CLOCR-C: Context Leveraging OCR Correction with Pre-trained Language Modelscited by 5
  17. 2026Red Skills or Blue Skills? A Dive Into Skills Published on ClawHubcited by 5
  18. 2023Protect Your Prompts: Protocols for IP Protection in LLM Applicationscited by 4
  19. 2023Cost-Efficient Prompt Engineering for Unsupervised Entity Resolutioncited by 4
  20. 2023An Analysis on Large Language Models in Healthcare: A Case Study of BioBERTcited by 3
  21. 2023Enhancing Summarization Performance through Transformer-Based Prompt Engineering in Automated Medical Reportingcited by 3
  22. 2025Large Language Models for Bioinformaticscited by 3
  23. 2025An Agentic AI Workflow for Detecting Cognitive Concerns in Real-world Datacited by 3
  24. 2026OralAgent: Integrating Reasoning, Tools, and Knowledge for Interactive Dental Image Analysiscited by 3
  25. 2024Accuracy and Consistency of LLMs in the Registered Dietitian Exam: The Impact of Prompt Engineering and Knowledge Retrievalcited by 2
  26. 2024The Future of Intelligent Healthcare: A Systematic Analysis and Discussion on the Integration and Impact of Robots Using Large Language Models for Healthcarecited by 2
  27. 2025Large Language Model-Based Generation of Discharge Summariescited by 2
  28. 2024Thematic Analysis with Large Language Models: does it work with languages other than English? A targeted test in Italiancited by 1
  29. 2024Towards Efficient Patient Recruitment for Clinical Trials: Application of a Prompt-Based Learning Modelcited by 1
  30. 2024A Prompt Engineering Approach and a Knowledge Graph based Framework for Tackling Legal Implications of Large Language Model Answerscited by 1
  31. 2025Language-Enhanced Generative Modeling for Amyloid PET Synthesis from MRI and Blood Biomarkerscited by 1
  32. 2026Improving Medical Visual Reinforcement Fine-Tuning via Perception and Reasoning Augmentationcited by 1
  33. 2024Effects of Different Prompts on the Quality of GPT-4 Responses to Dementia Care Questionscited by 0
  34. 2024Towards Fairer Health Recommendations: finding informative unbiased samples via Word Sense Disambiguationcited by 0
  35. 2024On Fusing ChatGPT and Ensemble Learning in Discon-tinuous Named Entity Recognition in Health Corporacited by 0
  36. 2025Multi-modal Knowledge Graph Generation with Semantics-enriched Promptscited by 0
  37. 2025LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documentscited by 0
  38. 2025The Limits of Goal-Setting Theory in LLM-Driven Assessmentcited by 0

50 most cited of 52 All 52 (JSON)