Published on in Vol 8, No 12 (2021): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/30439, first published .
Language, Speech, and Facial Expression Features for Artificial Intelligence–Based Detection of Cancer Survivors’ Depression: Scoping Meta-Review

Language, Speech, and Facial Expression Features for Artificial Intelligence–Based Detection of Cancer Survivors’ Depression: Scoping Meta-Review

Language, Speech, and Facial Expression Features for Artificial Intelligence–Based Detection of Cancer Survivors’ Depression: Scoping Meta-Review

Journals

  1. Lin B, Tan Z, Mo Y, Yang X, Liu Y, Xu B. Intelligent oncology: The convergence of artificial intelligence and oncology. Journal of the National Cancer Center 2023;3(1):83 View
  2. Arioz U, Smrke U, Plohl N, Mlakar I. Scoping Review on the Multimodal Classification of Depression and Experimental Study on Existing Multimodal Models. Diagnostics 2022;12(11):2683 View
  3. Yasin S, Othmani A, Raza I, Hussain S. Machine learning based approaches for clinical and non-clinical depression recognition and depression relapse prediction using audiovisual and EEG modalities: A comprehensive review. Computers in Biology and Medicine 2023;159:106741 View
  4. Chen Z, Kulkarni P, Galatzer-Levy I, Bigio B, Nasca C, Zhang Y. Modern views of machine learning for precision psychiatry. Patterns 2022;3(11):100602 View
  5. Wang H, Lin H, Liu B. Research progress on the psychological burden and intervention measures in cancer patients. Frontiers in Psychiatry 2024;15 View

Books/Policy Documents

  1. Gómez-Zaragozá L, Minissi M, Llanes-Jurado J, Altozano A, Alcañiz Raya M, Marín-Morales J. Collaborative Networks in Digitalization and Society 5.0. View
  2. Konstantopoulos K, Giakoumettis D. Neuroimaging in Neurogenic Communication Disorders. View