Artificial intelligence technologies for patient rehabilitation after systemic anticancer therapy

Globally, malignant neoplasms remain one of the most significant medical and social issues due to their increasing incidence.

Meanwhile, advances in early diagnosis and treatment methods have resulted in higher rates of long-term or complete remission among patients. Thus, medical rehabilitation for cancer patients becomes an important and relevant concern. As part of the modern treatment of malignant tumors, surgical intervention is often accompanied by systemic drug therapy, radiation therapy, or a combination of these approaches. Despite their high efficacy, these methods may result in long-term functional impairments. The most common complications include reduced physical activity, chronic fatigue, cognitive impairment, and other conditions that decrease patients’ quality of life. Recent studies emphasize the application of artificial intelligence (AI) technologies in medicine, including rehabilitation. Machine learning algorithms, biomedical data analysis systems, wearable devices, and digital platforms make it possible to monitor patients' conditions, thus individualizing rehabilitation programs. These technologies are therefore considered a promising approach to improving the effectiveness of rehabilitation for patients after anticancer treatment. This review discusses current approaches to using AI technologies to rehabilitate cancer patients after treatment. Particularly, it covers digital monitoring, telerehabilitation, systems for analyzing motor activity, and cognitive rehabilitation. The review also outlines prospects for further developing these technologies.

1. Shuel S.L. Targeted cancer therapies: clinical pearls for primary care. Can Fam Physician. 2022; 68 (7): 515–8. https://doi.org/10.46747/cfp.6807515.

2. Tan S., Li D., Zhu X. Cancer immunotherapy: pros, cons and beyond. Biomed Pharmacother. 2020; 124: 109821. https://doi.org/10.1016/j.biopha.2020.109821.

3. Basak D., Arrighi S., Darwiche Y., Deb S. Comparison of anticancer drug toxicities: paradigm shift in adverse effect profile. Life. 2021; 12 (1): 48. https://doi.org/10.3390/life12010048.

4. Anand U., Dey A., Chandel A.K.S., et al. Cancer chemotherapy and beyond: current status, drug candidates, associated risks and progress in targeted therapeutics. Genes Dis. 2023; 10 (4): 1367–401. https://doi.org/10.1016/j.gendis.2022.02.007.

5. Tilsed C.M., Fisher S.A., Nowak A.K., et al. Cancer chemotherapy: insights into cellular and tumor microenvironmental mechanisms of action. Front Oncol. 2022; 12: 960317. https://doi.org/10.3389/fonc.2022.960317.

6. Vasilyeva E.B., Rostovtsev D.M., Tolpeikina K.A., et al. Clinical experience in the neoadjuvant treatment of unresectable differentiated thyroid cancer with the lenvatinib. Opukholi golovy i shei / Head and Neck Tumors. 2024; 14 (1): 10–5 (in Russ.). https://doi.org/10.17650/2222-1468-2024-14-1-10-15.

7. Astolfi L., Ghiselli S., Guaran V., et al. Correlation of adverse effects of cisplatin administration in patients affected by solid tumours: a retrospective evaluation. Oncol Rep. 2013; 29 (4): 1285–92. https://doi.org/10.3892/or.2013.2279.

8. Radeva L., Yoncheva K. Doxorubicin toxicity and recent approaches to alleviating its adverse effects with focus on oxidative stress. Molecules. 2025; 30 (15): 3311. https://doi.org/10.3390/molecules30153311.

9. Lai J.I., Chao T.C., Liu C.Y., et al. A systemic review of taxanes and their side effects in metastatic breast cancer. Front Oncol. 2022; 12: 940239. https://doi.org/10.3389/fonc.2022.940239.

10. Macdonald J.S. Toxicity of 5-fluorouracil. Oncology. 1999; 13 (7 Suppl. 3): 33–4.

11. Ahles T.A., Saykin A.J. Candidate mechanisms for chemotherapyinduced cognitive changes. Nat Rev Cancer. 2007; 7 (3): 192–201. https://doi.org/10.1038/nrc2073.

12. Montoya S., Soong D., Nguyen N., et al. Targeted therapies in cancer: to be or not to be, selective. Biomedicines. 2021; 9 (11): 1591. https://doi.org/10.3390/biomedicines9111591.

13. Press M.F., Lenz H.J. EGFR, HER2 and VEGF pathways: validated targets for cancer treatment. Drugs. 2007; 67 (14): 2045–75. https://doi.org/10.2165/00003495-200767140-00006.

14. Hirsh V. Managing treatment-related adverse events associated with EGFR tyrosine kinase inhibitors in advanced non-small-cell lung cancer. Curr Oncol. 2011; 18 (3): 126–38. https://doi.org/10.3747/co.v18i3.877.

15. Schmidinger M. Understanding and managing toxicities of vascular endothelial growth factor (VEGF) inhibitors. EJC Suppl. 2013; 11 (2): 172–91. https://doi.org/10.1016/j.ejcsup.2013.07.016.

16. Dawoud E., Azribi F., Chehal A., et al. Monitoring and management of adverse effects associated with trastuzumab deruxtecan: a UAE-specific consensus. Front Oncol. 2025; 14: 1443962. https://doi.org/10.3389/fonc.2024.1443962.

17. Kzyrgalin Sh.R., Yamidanov R.S., Nazmieva K.A., Gantsev Sh.Kh. Review of small molecule anticancer NF-κB inhibitors. Creative Surgery and Oncology. 2023; 13 (2): 143–50 (in Russ.). https://doi.org/10.24060/2076-3093-2023-13-2-143-150.

18. Esfahani K., Roudaia L., Buhlaiga N., et al. A review of cancer immunotherapy: from the past, to the present, to the future. Curr Oncol. 2020; 27 (Suppl. 2): S87–97. https://doi.org/10.3747/co.27.5223.

19. Avdeeva Zh.I., Soldatov A.A., Alpatova N.A. et al. Studies on the immunogenicity of therapeutic proteins: methodological aspects of identifying and studying of the anti-drug antibodies. Immunologiya. 2024; 45 (1): 91–106 (in Russ.). https://doi.org/10.33029/1816-21342024-45-1-91-106.

20. Yin Q., Wu L., Han L., et al. Immune-related adverse events of immune checkpoint inhibitors: a review. Front Immunol. 2023; 14: 1167975. https://doi.org/10.3389/fimmu.2023.1167975.

21. Tremont A., Lu J., Cole J.T. Endocrine therapy for early breast cancer: updated review. Ochsner J. 2017; 17 (4): 405–11.

22. Connolly R.M., Carducci M.A., Antonarakis E.S. Use of androgen deprivation therapy in prostate cancer: indications and prevalence. Asian J Androl. 2012; 14 (2): 177–86. https://doi.org/10.1038/aja.2011.103.

23. Andreu Y., Soto-Rubio A., Ramos-Campos M., et al. Impact of hormone therapy side effects on health-related quality of life, distress, and well-being of breast cancer survivors. Sci Rep. 2022; 12 (1): 18673. https://doi.org/10.1038/s41598-022-22971-x.

24. Smith S.R., Zheng J.Y., Silver J., et al. Cancer rehabilitation as an essential component of quality care and survivorship from an international perspective. Disabil Rehabil. 2020; 42 (1): 8–13. https://doi.org/10.1080/09638288.2018.1514662.

25. Campbell K.L., Winters-Stone K.M., Wiskemann J., et al. Exercise guidelines for cancer survivors: consensus statement from international multidisciplinary roundtable. Med Sci Sports Exerc. 2019; 51 (11): 2375–90. https://doi.org/10.1249/MSS.0000000000002116

26. Miroshnikova A.S., Petrichenko А.V., Ostreikov I.F., et al. Achieving positive rehabilitation outcomes in a child with Von Hippel–Lindau disease following complete resection of a cerebellar hemangioblastoma: a case report. Physical and Rehabilitation Medicine, Medical Rehabilitation. 2025; 7 (4): 313–22 (in Russ.). https://doi.org/10.36425/rehab694067.

27. Aringazina A.M., Olzhayev S.T., Khegay B.S. Rehabilitation in oncology. Russian Journal of Preventive Medicine. 2019; 22 (5): 131–5 (in Russ.). https://doi.org/10.17116/profmed201922051131.

28. Wang L., Ho M.H., Choi E.P.H., et al. Effectiveness of cognitive rehabilitation in improving subjective and objective cognitive functions in cancer patients: a systematic review, pairwise, and network meta-analysis of randomized controlled trials. Int J Nurs Stud. 2026; 174: 105298. https://doi.org/10.1016/j.ijnurstu.2025.105298.

29. Weis J. Psychosocial care for cancer patients. Breast Care. 2015; 10 (2): 84–6. https://doi.org/10.1159/000381969.

30. Basch E., Deal A.M., Dueck A.C., et al. Overall survival results of a trial assessing patient-reported outcomes for symptom monitoring during routine cancer treatment. JAMA. 2017; 318 (2): 197–8. https://doi.org/10.1001/jama.2017.7156.

31. Murashko M.A., Vankov V.V., Panin A.I., et al. Implementation of artificial intelligence technologies in healthcare in Russia: results of 2024. National Health Care (Russia). 2025; 6 (3): 6–19 (in Russ.). https://doi.org/10.47093/2713-069X.2025.6.3.6-19.

32. Korabelnikov D.I., Lamotkin A.I. Artificial intelligence in oncology: global experience and future prospects. FARMAKOEKONOMIKA. Sovremennaya farmakoekonomika i farmakoepidemiologiya / FARMAKOEKONOMIKA. Modern Pharmacoeconomics and Pharmacoepidemiology. 2025; 18 (3): 437–47 (in Russ.). https://doi.org/10.17749/2070-4909/farmakoekonomika.2025.302.

33. Sufelfa A.R., Petrishcheva K.N., Shcherbina K.K., et al. Artificial intelligence in comprehensive rehabilitation of people with disabilities. (Literature review). Problems of Balneology, Physiotherapy and Exercise Therapy. 2025; 102 (3): 54–61 (in Russ.). https://doi.org/10.17116/kurort202510203154.

34. Hao J. Harnessing artificial intelligence for cancer rehabilitation: a call to action. Support Care Cancer. 2025; 33 (11): 961. https://doi.org/10.1007/s00520-025-10047-1.

35. Piwek L., Ellis D.A., Andrews S., Joinson A. The rise of consumer health wearables: promises and barriers. PLoS Med. 2016; 13 (2): e1001953. https://doi.org/10.1371/journal.pmed.1001953.

36. Topol E.J. High-performance medicine: the convergence of human and artificial intelligence. Nat Med. 2019; 25 (1): 44–56. https://doi.org/10.1038/s41591-018-0300-7.

37. Goncalves Leite Rocco P., Reategui-Rivera C.M., Finkelstein J. Telemedicine applications for cancer rehabilitation: scoping review. JMIR Cancer. 2024; 10: e56969. https://doi.org/10.2196/56969.

38. Batalik L., Chamradova K., Winnige P., et al. Effect of exercise-based cancer rehabilitation via telehealth: a systematic review and metaanalysis. BMC Cancer. 2024; 24 (1): 600. https://doi.org/10.1186/s12885-024-12348-w.

39. Dennett A., Harding K.E., Reimert J., et al. Telerehabilitation's safety, feasibility, and exercise uptake in cancer survivors: process evaluation. JMIR Cancer. 2021; 7 (4): e33130. https://doi.org/10.2196/33130.

40. Sumner J., Lim H.W., Chong L.S., et al. Artificial intelligence in physical rehabilitation: a systematic review. Artif Intell Med. 2023; 146: 102693. https://doi.org/10.1016/j.artmed.2023.102693.

41. Capetti B., Sdinami S., Luisi J., et al. Efficacy of technology-based cognitive rehabilitation tools for cancer-related cognitive impairment in non-CNS cancer patients: a systematic review. Healthcare. 2026; 14 (2): 239. https://doi.org/10.3390/healthcare14020239.

42. Zeng Y., Zeng L., Cheng A.S.K., et al. The use of immersive virtual reality for cancer-related cognitive impairment assessment and rehabilitation: a clinical feasibility study. Asia Pac J Oncol Nurs. 2022; 9 (12): 100079. https://doi.org/10.1016/j.apjon.2022.100079.