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A Short Review of Ethical Challenges in Clinical Natural Language Processing

arXiv 1703.10090 ↗First posted 29 Mar 2017cs.CL cs.CYcited by 14

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Abstract (arXiv)

Clinical NLP has an immense potential in contributing to how clinical practice will be revolutionized by the advent of large scale processing of clinical records. However, this potential has remained largely untapped due to slow progress primarily caused by strict data access policies for researchers. In this paper, we discuss the concern for privacy and the measures it entails. We also suggest sources of less sensitive data. Finally, we draw attention to biases that can compromise the validity of empirical research and lead to socially harmful applications.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 Mar 2017.

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Citing papers per year: 2021: 2; 2022: 5; 2023: 3; 2024: 1; 2025: 3.

14 papers.

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  1. 2021PsyQA: A Chinese Dataset for Generating Long Counseling Text for Mental Health Supportcited by 92
  2. 2023Analyzing Dataset Annotation Quality Management in the Wildcited by 39
  3. 2022PQLM -- Multilingual Decentralized Portable Quantum Language Model for Privacy Protectioncited by 26
  4. 2024Still Not Quite There! Evaluating Large Language Models for Comorbid Mental Health Diagnosiscited by 12
  5. 2022MentSum: A Resource for Exploring Summarization of Mental Health Online Postscited by 11
  6. 2023FedTherapist: Mental Health Monitoring with User-Generated Linguistic Expressions on Smartphones via Federated Learningcited by 10
  7. 2023Exploring the Landscape of Natural Language Processing Researchcited by 7
  8. 2022Resources for Turkish Natural Language Processing: A critical surveycited by 6
  9. 2022Prompt Combines Paraphrase: Teaching Pre-trained Models to Understand Rare Biomedical Wordscited by 6
  10. 2025Adversarial Attacks on AI-Generated Text Detection Models: A Token Probability-Based Approach Using Embeddingscited by 5
  11. 2021Use of Formal Ethical Reviews in NLP Literature: Historical Trends and Current Practicescited by 3
  12. 2022Is Your Model Sensitive? SPeDaC: A New Benchmark for Detecting and Classifying Sensitive Personal Datacited by 3
2 more
  1. 2025MedOrchestra: A Hybrid Cloud-Local LLM Approach for Clinical Data Interpretationcited by 0
  2. 2025HealthcareNLP: where are we and what is next?cited by 0