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

Reviews in Digital Mental Health (265) Depression and Mood Disorders; Suicide Prevention (1541) Diagnostic Tools in Mental Health (284) Artificial Intelligence (1786) mHealth for Screening (265) Cancer Survivorship (289) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1850) Emotional, Social, Psychological Support for Cancer (221) Speech and Phonetics in Verbal Protocols (Think Aloud, Recall, and Explanation Tasks) (94)

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

Authors of this article:

Urška Smrke1 Author Orcid Image ;   Izidor Mlakar1 Author Orcid Image ;   Simon Lin2, 3 Author Orcid Image ;   Bojan Musil4 Author Orcid Image ;   Nejc Plohl4 Author Orcid Image
Article Authors Cited by (15) Tweetations (7) Metrics

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
  6. Mlakar I, Arioz U, Smrke U, Plohl N, Šafran V, Rojc M. An End-to-End framework for extracting observable cues of depression from diary recordings. Expert Systems with Applications 2024;257:125025 View
  7. Das K, Gavade P. A review on the efficacy of artificial intelligence for managing anxiety disorders. Frontiers in Artificial Intelligence 2024;7 View
  8. Smrke U, Mlakar I, Rehberger A, Žužek L, Plohl N. Decoding anxiety: A scoping review of observable cues. DIGITAL HEALTH 2024;10 View
  9. Goh Y, See Q, Vongsirimas N, Klanin‐Yobas P. Artificial Intelligence in Diagnosing Depression Through Behavioural Cues: A Diagnostic Accuracy Systematic Review and Meta‐Analysis. Journal of Clinical Nursing 2025 View
  10. Rony M, Das D, Khatun M, Ferdousi S, Akter M, Khatun M, Begum M, Khalil M, Parvin M, Alrazeeni D, Akter F. Artificial intelligence in psychiatry: A systematic review and meta-analysis of diagnostic and therapeutic efficacy. DIGITAL HEALTH 2025;11 View
  11. Bires J, Franklin E, Nelson K, Bonesteel K, Flora D. Exploring the Intersection of Artificial Intelligence and Psychosocial Oncology: Enhancing Care in the Digital Age. AI in Precision Oncology 2025;2(3):80 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

Conference Proceedings

  1. Jindal S, Jindal M, Bhati P. 2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST). Artificial Intelligence in cancer survivorship care plans: what lies beyond diagnostics? View
  2. Smrke U, Mlakar I, Arioz U, Plohl N. INTERNATIONAL CONFERENCE OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING ICCMSE 2022. Artificial intelligence-based detection of cancer survivors’ depression cues: A narrative review View