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HealthcareNLP: where are we and what is next?

arXiv 2512.08617 ↗First posted 9 Dec 2025cs.CLcited by 0

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Abstract (arXiv)

This tutorial focused on Healthcare Domain Applications of NLP, what we have achieved around HealthcareNLP, and the challenges that lie ahead for the future. Existing reviews in this domain either overlook some important tasks, such as synthetic data generation for addressing privacy concerns, or explainable clinical NLP for improved integration and implementation, or fail to mention important methodologies, including retrieval augmented generation and the neural symbolic integration of LLMs and KGs. In light of this, the goal of this tutorial is to provide an introductory overview of the most important sub-areas of a patient- and resource-oriented HealthcareNLP, with three layers of hierarchy: data/resource layer: annotation guidelines, ethical approvals, governance, synthetic data; NLP-Eval layer: NLP tasks such as NER, RE, sentiment analysis, and linking/coding with categorised methods, leading to explainable HealthAI; patients layer: Patient Public Involvement and Engagement (PPIE), health literacy, translation, simplification, and summarisation (also NLP tasks), and shared decision-making support. A hands-on session will be included in the tutorial for the audience to use HealthcareNLP applications. The target audience includes NLP practitioners in the healthcare application domain, NLP researchers who are interested in domain applications, healthcare researchers, and students from NLP fields. The type of tutorial is "Introductory to CL/NLP topics (HealthcareNLP)" and the audience does not need prior knowledge to attend this. Tutorial materials: https://github.com/4dpicture/HealthNLP

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 18 of its 77 references that are in the map. First posted on arXiv 9 Dec 2025.

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18 of 77 references.

References · 18

  1. 2022A Survey on In-context Learningcited by 717
  2. 2020Self-Alignment Pretraining for Biomedical Entity Representationscited by 233
  3. 2023GPT-NER: Named Entity Recognition via Large Language Modelscited by 158
  4. 2023Large language models in healthcare and medical domain: A reviewcited by 126
  5. 2020Explainable Automated Coding of Clinical Notes using Hierarchical Label-wise Attention Networks and Label Embedding Initialisationcited by 38
  6. 2022A Dataset for Plain Language Adaptation of Biomedical Abstractscited by 19
  7. 2017A Short Review of Ethical Challenges in Clinical Natural Language Processingcited by 14
  8. 2023Investigating Large Language Models and Control Mechanisms to Improve Text Readability of Biomedical Abstractscited by 8
  9. 2020SemClinBr -- a multi institutional and multi specialty semantically annotated corpus for Portuguese clinical NLP taskscited by 7
  10. 2024Exploration of Masked and Causal Language Modelling for Text Generationcited by 7
  11. 2019Federated Learning for Healthcare Informaticscited by 6
  12. 2025MaLei at MultiClinSUM: Summarisation of Clinical Documents using Perspective-Aware Iterative Self-Prompting with LLMscited by 6
6 more
  1. 2024It's Difficult to be Neutral -- Human and LLM-based Sentiment Annotation of Patient Commentscited by 4
  2. 2023Generating Medical Prescriptions with Conditional Transformercited by 3
  3. 2025Dutch Metaphor Extraction from Cancer Patients' Interviews and Forum Data using LLMs and Human in the Loopcited by 3
  4. 2024Biomedical Entity Linking for Dutch: Fine-tuning a Self-alignment BERT Model on an Automatically Generated Wikipedia Corpuscited by 1
  5. 2025Mixed Feelings: Cross-Domain Sentiment Classification of Patient Feedbackcited by 1
  6. 2025Lessons from the TREC Plain Language Adaptation of Biomedical Abstracts (PLABA) trackcited by 1

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  1. 2026Generating High Quality Synthetic Data for Dutch Medical Conversations
  2. 2023README: Bridging Medical Jargon and Lay Understanding for Patient Education through Data-Centric NLP
  3. 2025Exploring Large Language Models in Healthcare: Insights into Corpora Sources, Customization Strategies, and Evaluation Metrics
  4. 2024Rephrasing Electronic Health Records for Pretraining Clinical Language Models
  5. 2026A primer on evaluation methods for large language models in healthcare
  6. 2024SemEval-2024 Task 2: Safe Biomedical Natural Language Inference for Clinical Trials
  7. 2026LLM-as-a-Judge in Healthcare: A Scoping Analysis of Applications, Methods, and Human Alignment ↗
  8. 2024HealthQ: Unveiling Questioning Capabilities of LLM Chains in Healthcare Conversations