Page 139 - EJMO-9-1

Eurasian Journal of Medicine and
Oncology
Oncology care with AI chatbots and assistants

Table 6. Key projections of AI evolution over the next decade
Area of evolution Predicted trends
Multi-modal data integration Real-time synthesis of genomic, imaging, clinical, and environmental data to enable precision medicine.
Predictive AI models and early warning Machine learning models for early detection of chemotherapy resistance, relapse, and side effects.
systems
Wearable health monitoring devices Continuous AI integration with wearable devices for real-time health tracking and early intervention.
AI-driven robotic surgery Enhanced imaging-guided robotic surgery with machine learning for better tumor targeting and less trauma.
Ethics and AI governance Improved transparency, bias mitigation, and ethical use of AI in clinical care.
Abbreviation: AI: Artificial intelligence.

technological innovation. These advancements will allow to ensure coordinated care and timely interventions.
oncologists to practice a more personalized, efficient, and Furthermore, as AI technology evolves, it will help bridge
data-informed model of cancer care while maintaining gaps in healthcare access, particularly for underserved
ethical oversight and human involvement. populations, by offering multilingual support and enhancing
Balancing these technological developments with telemedicine capabilities. However, challenges, such as
clinical workflows and ethical principles will ensure that ensuring data security, reducing bias, and maintaining
AI continues to enhance – not replace – compassionate, patient trust, must be addressed. By continuously refining
personalized cancer care. these systems, AI virtual assistants will increasingly play a
crucial role in enhancing patient care, supporting healthcare
7. Conclusion providers, and improving the overall cancer care experience.

AI-powered virtual assistants and chatbots present a promising Acknowledgments
approach to improve patient support in oncology care. Their
ability to offer personalized, immediate, and emotionally None.
supportive interactions enhances the patient experience, Funding
especially in managing the physical and psychological
challenges of cancer treatment. By offering continuous, real- None.
time access to information, these systems empower patients to
make informed decisions about their care, thereby improving Conflict of interest
treatment adherence and clinical outcomes. However, while All the authors declare they have no competing interests.
these tools can efficiently handle routine inquiries and provide
vital emotional support, they cannot replace the nuanced care Author contributions
provided by human oncologists, especially in complex cases. Conceptualization: Hemalatha Senthilmahesh
Therefore, the integration of AI into oncology care must be
seen as a complement, rather than a replacement, to human Data curation: Muthuvairavan Pillai Nagappan
healthcare providers. Ensuring data privacy, maintaining Investigation: Hemalatha Senthilmahesh
continuous system updates, and fostering patient trust will Methodology: Hemalatha Senthilmahesh
Resources: Somavarapu N.C. Shekhar
be critical for the widespread adoption of AI-driven solutions
in oncology. Moving forward, AI’s role in oncology care will Validation: Pullela SVVSR Kumar
continue to evolve, with future advancements poised to further Visualization: Anbarasa A. Pandian
enhance its ability to provide personalized, compassionate, Writing – original draft: Hemalatha Senthilmahesh
and efficient patient support. Writing – review & editing: Ramesh Tumaati
The future of AI-powered virtual assistants and chatbots Ethics approval and consent to participate
in oncology is promising, with advancements in AI, ML, Not applicable.
and NLP set to enhance their ability to provide personalized,
empathetic, and real-time support for cancer patients. Consent for publication
Future developments will focus on improving emotional
intelligence, integrating with wearable devices for real- Not applicable.
time health monitoring, and offering predictive insights for Availability of data
better symptom management. AI systems will also be more
seamlessly integrated with healthcare provider platforms Not applicable.

Volume 9 Issue 1 (2025) 131 doi: 10.36922/ejmo.6251