Published on in Vol 7, No 4 (2019): Oct-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/14401, first published .
Characterizing Artificial Intelligence Applications in Cancer Research: A Latent Dirichlet Allocation Analysis

Characterizing Artificial Intelligence Applications in Cancer Research: A Latent Dirichlet Allocation Analysis

Characterizing Artificial Intelligence Applications in Cancer Research: A Latent Dirichlet Allocation Analysis

Journals

  1. Sharafeldin N, Richman J, Bosworth A, Chen Y, Singh P, Patel S, Wang X, Francisco L, Forman S, Wong F, Bhatia S. Clinical and Genetic Risk Prediction of Cognitive Impairment After Blood or Marrow Transplantation for Hematologic Malignancy. Journal of Clinical Oncology 2020;38(12):1312 View
  2. Sperandeo R, Messina G, Iennaco D, Sessa F, Russo V, Polito R, Monda V, Monda M, Messina A, Mosca L, Mosca L, Dell'Orco S, Moretto E, Gigante E, Chiacchio A, Scognamiglio C, Carotenuto M, Maldonato N. What Does Personality Mean in the Context of Mental Health? A Topic Modeling Approach Based on Abstracts Published in Pubmed Over the Last 5 Years. Frontiers in Psychiatry 2020;10 View
  3. Li Y, Zhang T, Yang Y, Gao Y. Artificial intelligence-aided decision support in paediatrics clinical diagnosis: development and future prospects. Journal of International Medical Research 2020;48(9) View
  4. Javaid M, Haleem A, Khan I, Vaishya R, Vaish A. Extending Capabilities of Artificial Intelligence for Decision-Making and Healthcare Education. Apollo Medicine 2020;17(1):53 View
  5. Kulakli A, Shubina I. Scientific Publication Patterns of Mobile Technologies and Apps for Posttraumatic Stress Disorder Treatment: Bibliometric Co-Word Analysis. JMIR mHealth and uHealth 2020;8(11):e19391 View
  6. He Q, Du F, Simonse L. A Patient Journey Map to Improve the Home Isolation Experience of Persons With Mild COVID-19: Design Research for Service Touchpoints of Artificial Intelligence in eHealth. JMIR Medical Informatics 2021;9(4):e23238 View
  7. Li X, Wang C, Sheng Y, Zhang J, Wang W, Yin F, Wu Q, Wu Q, Ge Y. An artificial intelligence‐driven agent for real‐time head‐and‐neck IMRT plan generation using conditional generative adversarial network (cGAN). Medical Physics 2021;48(6):2714 View
  8. Wang K, Zheng C, Xue L, Deng D, Zeng L, Li M, Deng X. A bibliometric analysis of 16,826 triple-negative breast cancer publications using multiple machine learning algorithms: Progress in the past 17 years. Frontiers in Medicine 2023;10 View
  9. Xiao J, Mo M, Wang Z, Zhou C, Shen J, Yuan J, He Y, Zheng Y. The Application and Comparison of Machine Learning Models for the Prediction of Breast Cancer Prognosis: Retrospective Cohort Study. JMIR Medical Informatics 2022;10(2):e33440 View
  10. Mosallaie S, Rad M, Schiffauerova A, Ebadi A. Discovering the evolution of artificial intelligence in cancer research using dynamic topic modeling. COLLNET Journal of Scientometrics and Information Management 2021;15(2):225 View
  11. Neijzen D, Lunter G. Unsupervised learning for medical data: A review of probabilistic factorization methods. Statistics in Medicine 2023;42(30):5541 View
  12. Shah A, Lee K, Hidayat A, Falchook A, Muhammad W. A text analytics approach for mining public discussions in online cancer forum: Analysis of multi-intent lung cancer treatment dataset. International Journal of Medical Informatics 2024;184:105375 View
  13. Ghaddaripouri K, Ghaddaripouri M, Mousavi A, Mousavi Baigi S, Rezaei Sarsari M, Dahmardeh Kemmak F, Mazaheri Habibi M. The effect of machine learning algorithms in the prediction, and diagnosis of meningitis: A systematic review. Health Science Reports 2024;7(2) View
  14. Lopez-Perez L, Georga E, Conti C, Vicente V, García R, Pecchia L, Fotiadis D, Licitra L, Cabrera M, Arredondo M, Fico G. Statistical and machine learning methods for cancer research and clinical practice: A systematic review. Biomedical Signal Processing and Control 2024;92:106067 View
  15. Kevlishvili I, St. Michel R, Garrison A, Toney J, Adamji H, Jia H, Román-Leshkov Y, Kulik H. Leveraging natural language processing to curate the tmCAT, tmPHOTO, tmBIO, and tmSCO datasets of functional transition metal complexes. Faraday Discussions 2025 View
  16. Zhang Y, Yu C, Zhao F, Xu H, Zhu C, Li Y. Landscape of Artificial Intelligence in Breast Cancer (2000–2021): A Bibliometric Analysis. Frontiers in Bioscience-Landmark 2022;27(8) View

Books/Policy Documents

  1. Moloi T, Marwala T. Artificial Intelligence and the Changing Nature of Corporations. View
  2. Dlamini Z, Hull R, Marima R, Skepu A, Makrogkikas S, Koumoulos E, Bakas G, Vamvakaris I, Syrigos K, Evangelou G, Kavidopoulou A, Lolas G. Trends of Artificial Intelligence and Big Data for E-Health. View