Published on in Vol 12 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/51925, first published .
Predicting Depression Risk in Patients With Cancer Using Multimodal Data: Algorithm Development Study

Predicting Depression Risk in Patients With Cancer Using Multimodal Data: Algorithm Development Study

Predicting Depression Risk in Patients With Cancer Using Multimodal Data: Algorithm Development Study

Journals

  1. Drobotun O, Kolotilov N, Konovalenko V, Konovalenko S, Ternovyy N. COMORBIDITY IN ONCOLOGY: MODERN CHALLENGES AND THE SEARCH FOR WAYS TO SOLVE THE PROBLEM. Clinical and Preventive Medicine 2024;(3):132 View
  2. van Buchem M, de Hond A, Fanconi C, Shah V, Schuessler M, Kant I, Steyerberg E, Hernandez-Boussard T. Applying natural language processing to patient messages to identify depression concerns in cancer patients. Journal of the American Medical Informatics Association 2024;31(10):2255 View
  3. Priego-Parra B, Remes-Troche J. Bidirectional relationship between gastrointestinal cancer and depression: The key is in the microbiota-gut-brain axis. World Journal of Gastroenterology 2024;30(48):5104 View
  4. Wang M, Fan S, Li Y, Gao B, Xie Z, Chen H. Robust multi-modal fusion architecture for medical data with knowledge distillation. Computer Methods and Programs in Biomedicine 2025;260:108568 View

Books/Policy Documents

  1. Irmak-Yazicioglu M, Arslan A. Recent Advances and Challenges in the Treatment of Major Depressive Disorder. View