This paper is in the following e-collection/theme issue:

Reviews in Medical Informatics (104) Artificial Intelligence (1966) Clinical Information and Decision Making (1789) Imaging Informatics (275) Innovations in Cancer Diagnostic and Decision Support (95)

Published on in Vol 9, No 6 (2021): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26601, first published .
Hyperpolarized Magnetic Resonance and Artificial Intelligence: Frontiers of Imaging in Pancreatic Cancer

Hyperpolarized Magnetic Resonance and Artificial Intelligence: Frontiers of Imaging in Pancreatic Cancer

Hyperpolarized Magnetic Resonance and Artificial Intelligence: Frontiers of Imaging in Pancreatic Cancer

Authors of this article:

José S Enriquez1, 2 Author Orcid Image ;   Yan Chu3 Author Orcid Image ;   Shivanand Pudakalakatti1 Author Orcid Image ;   Kang Lin Hsieh3 Author Orcid Image ;   Duncan Salmon4 Author Orcid Image ;   Prasanta Dutta1 Author Orcid Image ;   Niki Zacharias Millward2, 5 Author Orcid Image ;   Eugene Lurie6 Author Orcid Image ;   Steven Millward1, 2 Author Orcid Image ;   Florencia McAllister2, 7 Author Orcid Image ;   Anirban Maitra2, 8 Author Orcid Image ;   Subrata Sen2, 6 Author Orcid Image ;   Ann Killary2, 6 Author Orcid Image ;   Jian Zhang9 Author Orcid Image ;   Xiaoqian Jiang3 Author Orcid Image ;   Pratip K Bhattacharya1, 2 Author Orcid Image ;   Shayan Shams3 Author Orcid Image
Article Authors Cited by (11) Tweetations (7) Metrics

Journals

  1. Yin H, Zhang F, Yang X, Meng X, Miao Y, Noor Hussain M, Yang L, Li Z. Research trends of artificial intelligence in pancreatic cancer: a bibliometric analysis. Frontiers in Oncology 2022;12 View
  2. Hameed B, Krishnan U. Artificial Intelligence-Driven Diagnosis of Pancreatic Cancer. Cancers 2022;14(21):5382 View
  3. Chen J, Chen R, Chau C, Sedgwick A, Xue Q, Chen T, Zeng S, Chen N, Wong K, Song L, Ren Y, Yang J, Sessler J, Liu C. Targeted Cyclo[8]pyrrole-Based NIR-II Photoacoustic Tomography Probe for Suppression of Orthotopic Pancreatic Tumor Growth and Intra-abdominal Metastases. Journal of the American Chemical Society 2024;146(7):4620 View
  4. Anghel C, Grasu M, Anghel D, Rusu-Munteanu G, Dumitru R, Lupescu I. Pancreatic Adenocarcinoma: Imaging Modalities and the Role of Artificial Intelligence in Analyzing CT and MRI Images. Diagnostics 2024;14(4):438 View
  5. Szymaszek P, Tyszka-Czochara M, Ortyl J. Application of Photoactive Compounds in Cancer Theranostics: Review on Recent Trends from Photoactive Chemistry to Artificial Intelligence. Molecules 2024;29(13):3164 View
  6. Shakerian N, Tafazoli A, Razavinia A, Sadrzadeh Aghajani Z, Bana N, Mard-Soltani M, Khalesi B, Hashemi Z, Khalili S. Current Understanding of Therapeutic and Diagnostic Applications of Exosomes in Pancreatic Cancer. Pancreas 2025;54(3):e255 View
  7. Wang H, Gui Y, Lv K. Molecular Imaging: Unveiling Metabolic Abnormalities in Pancreatic Cancer. International Journal of Molecular Sciences 2025;26(11):5242 View
  8. Khorsandi D, Farahani A, Zarepour A, Khosravi A, Iravani S, Zarrabi A. Bridging technology and medicine: artificial intelligence in targeted anticancer drug delivery. RSC Advances 2025;15(34):27795 View
  9. Yu X, Wang Y, Wang Y, Feng J, Fan S, Li C. Combining multimodal medical imaging and artificial intelligence for the early diagnosis of pancreatic cancer. Frontiers in Medicine 2025;12 View
  10. Seven İ, Çalişkan C, Köş F, Arslan H, Aktürk Esen S, Ceylan F, Uncu D. Predicting survival outcomes in advanced pancreatic cancer using machine learning methods. Medicine 2025;104(33):e43904 View

Conference Proceedings

  1. S A, Chelliah B. 2024 Third International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT). Early Prediction of Pancreatic Malignancy by using Deep Learning Techniques View