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Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/74231, first published .
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Classifying Patient Complaints Using Artificial Intelligence–Powered Large Language Models: Cross-Sectional Study

Classifying Patient Complaints Using Artificial Intelligence–Powered Large Language Models: Cross-Sectional Study

Journals

  1. Yang H, Li G, Zhao C. Artificial intelligence in the study of oral lichen planus characteristics: a review. BDJ Open 2025;11(1) View
  2. Teymourifar A. Defining an integrative multidimensional framework for patient complaint management systems. Frontiers in Health Services 2026;6 View
  3. Sulaiman M, Muda N. Automated triaging of hospital complaints using Large Language Model-Assisted Content Analysis and machine learning. Engineering Applications of Artificial Intelligence 2026;178:114942 View
  4. Akoglu B, Simsek A, Noor S. Parents’ Perspectives on Artificial Intelligence–Supported Pediatric Healthcare Services: A Descriptive and Correlational Study. Journal of Nursing Management 2026;2026(1) View
  5. Pérez-Jiménez A, Font Jiménez I, Hernández Fernández F. Reclamaciones de pacientes en atención primaria en una región española (2018-2024): un análisis cuantitativo. Atención Primaria 2026;58(9):103535 View
  6. Law T, Ting C, Ng H, Goh H. Enhancing complaint locations prediction with image-space embedding representations and customized large language models. Scientific Reports 2026;16(1) View
  7. Martinez J, Lopez C. Multimodal Neural Network for Predicting Patient Complaint Escalation Using Call Center Transcripts, Portal Messages, Service Recovery Notes, Encounter Metadata, and Prior Satisfaction Survey Responses. Journal of Health Informatics and Digital Systems 2026;6(1) View
  8. Law T, Ting C. Enriching structured dataset via reasoning embeddings with few-shot learning for enhancing complaint classification. Discover Artificial Intelligence 2026;6(1) View
  9. Lee C, Luo C, Zou J, Li F. A novel human-AI collaboration framework for service failure recovery and service quality enhancement with LLM-TRIZ integration. Journal of Engineering Design 2026:1 View

Books/Policy Documents

  1. Almado A, Alameri S, Hamdan E, Awni S, Al-Obaidi S, Hammadi A, Alyousuf A. Digital Marketing for Public Dental Health. View

Conference Proceedings

  1. Sharma V, Chaudhary P, Singh A, Kausahik P, Iqbal N. 2025 IEEE Pune Section International Conference (PuneCon). Resident Issue Reporting System with AI-Powered Predictive Analytics and Blockchain Transparency View