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Cancer Prognosis Models and Machine Learning (82) Artificial Intelligence (2365) Natural Language Processing (961) Generative Language Models Including ChatGPT (825) Imaging Informatics (334) Medical imaging (134) Lung Cancer (73)

Published on in Vol 11 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/57275, first published .
Large Language Model Approach for Zero-Shot Information Extraction and Clustering of Japanese Radiology Reports: Algorithm Development and Validation

Large Language Model Approach for Zero-Shot Information Extraction and Clustering of Japanese Radiology Reports: Algorithm Development and Validation

Large Language Model Approach for Zero-Shot Information Extraction and Clustering of Japanese Radiology Reports: Algorithm Development and Validation

Authors of this article:

Yosuke Yamagishi1 Author Orcid Image ;   Yuta Nakamura2 Author Orcid Image ;   Shouhei Hanaoka1 Author Orcid Image ;   Osamu Abe1 Author Orcid Image
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Journals

  1. Haixian L, Shu P, Zhao L, Chunfeng L, Lun L. Machine learning approaches for EGFR mutation status prediction in NSCLC: an updated systematic review. Frontiers in Oncology 2025;15 View
  2. Kang H, Li J, Hou L, Xu X, Zheng S, Li Q. Large Language Model–Enhanced Drug Repositioning Knowledge Extraction via Long Chain-of-Thought: Development and Evaluation Study. JMIR Medical Informatics 2025;13:e77837 View
  3. Zhong R, Chen S, Li Z, Gao T, Su Y, Zhang W, Liu D, Gao L, Hu K. Large Language Models in Lung Cancer: Systematic Review. Journal of Medical Internet Research 2025;27:e74177 View
  4. Yasaka K, Wada M, Tokuyama K, Takaishi T, Abe O. Impact of Super-Resolution Deep Learning Reconstruction on Low-Dose CT in Patients with Central Venous Catheter or Central Venous Port. Journal of Imaging Informatics in Medicine 2025 View
  5. Lee R, Hadidchi R, Coard M, Rubinov Y, Alamuri T, Liaw A, Chandrupatla R, Duong T. Use of Large Language Models on Radiology Reports: A Scoping Review. Journal of the American College of Radiology 2026;23(3):437 View
  6. May P, Greß J, Seidel C, Sommer S, Schuler M, Nokodian S, Schröder F, Jung J. Enabling Just-in-Time Clinical Oncology Analysis With Large Language Models: Feasibility and Validation Study Using Unstructured Synthetic Data. JMIR Medical Informatics 2025;13:e78332 View
  7. Li Z, Yang D, Li R, Zhang J. Knowledge-Guided and Reinforced Selective State Space Model for radiology report generation. Journal of Biomedical Informatics 2026;177:105011 View
  8. Suh P, Jeong S, Ueda D, Shim W, Heo H, Woo C, Park H, Suh C. Insufficient reporting quality in large language model studies in the field of radiology. Insights into Imaging 2026;17(1) View
  9. Abdulai H, Manresa-Yee C, Rexha H, Lafond S. Zero-shot evidence-grounded extraction of blood–brain barrier nanoparticle design parameters with open-weight language models. Machine Learning: Science and Technology 2026;7(2):025032 View

Conference Proceedings

  1. Bobde A, Ninawe J, Tandulkar R, Katulwar A, Kukade A. 2025 3rd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry (IDICAIHEI). Leveraging Pre-Trained Vision and Language Models for Zero-Shot Clinical Explanation Generation View