Health Technology/clinical-trials

Digital Pain Assessment Study Completed: Machine Learning Analysis of Facial and Voice Patterns in Cancer Patients — Clinical Implications for Pain Management

247 Health News Editorial

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9 Apr 2026

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4 min read

·clinical-trials

A completed NCI feasibility study demonstrates potential for machine learning to objectively assess cancer pain through facial and voice analysis. The 83-participant study offers new insights for digital pain management tools in oncology practice.

Originally reported by ClinicalTrials.gov

References

  1. 1.National Cancer Institute. (2024). A Feasibility Study Investigating the Use of Machine Learning to Analyze Facial Imaging, Voice and Spoken Language for the Capture and Classification of Cancer/Tumor Pain. ClinicalTrials.gov. https://clinicaltrials.gov/study/NCT04442425
  2. 2.Kunz, M., & Lautenbacher, S. (2022). Facial expressions of pain in patients with dementia: A systematic review. Pain Medicine, 23(7), 1319-1332. https://doi.org/10.1093/pm/pnab285
  3. 3.Tighe, P. J., Goldsmith, R. C., & Gravenstein, M. (2021). The convergence of artificial intelligence and pain medicine: A systematic review. Pain Medicine, 22(6), 1374-1382. https://doi.org/10.1093/pm/pnab094
  4. 4.van den Beuken-van Everdingen, M. H., Hochstenbach, L. M., Joosten, E. A., Tjan-Heijnen, V. C., & Janssen, D. J. (2016). Update on prevalence of pain in patients with cancer: Systematic review and meta-analysis. Journal of Pain and Symptom Management, 51(6), 1070-1090. https://doi.org/10.1016/j.jpainsymman.2015.12.340
  5. 5.Dworkin, R. H., Turk, D. C., Farrar, J. T., Haythornthwaite, J. A., Jensen, M. P., Katz, N. P., ... & Witter, J. (2005). Core outcome measures for chronic pain clinical trials: IMMPACT recommendations. Pain, 113(1-2), 9-19. https://doi.org/10.1016/j.pain.2004.09.012
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