Page 136 - EJMO-9-1

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

Table 5. Summary of measurable impacts of AI virtual assistants on key clinical outcomes
Metric Impact of AI virtual assistants Study/source
Reduction in missed appointments 30% reduction in missed oncology appointments due to AI Chen et al. 9
reminders
Medication adherence improvement 20% increase in medication adherence rates with AI reminders Lee et al. 17
Reduction in reported anxiety levels 35% reduction in anxiety levels due to emotional support Velindre University
chatbots NHS Trust, 2023
Increased engagement in telemedicine 25% increase in treatment adherence through telemedicine Chen et al. 9
consultations interventions
Abbreviation: AI: Artificial intelligence.

Similarly, while AI models can predict chemotherapy identify high-risk patients from historical data and send
resistance by identifying genomic risk factors, oncologists automated follow-up care notifications improve efficiency
must integrate this information with patient history, and ensure timely interventions.
overall health, and other clinical factors to tailor In addition, AI systems for real-time monitoring
treatment strategies. Human oversight ensures that and alerts continuously track vital signs, lab results,
these AI-generated insights are applied appropriately, and treatment schedules, triggering early interventions.
considering the complexities of individual patient care. However, these alerts require human judgment to
In handling emotional and psychological aspects, AI can determine the appropriate response. For instance, AI
provide basic support, but it falls short in addressing the systems monitoring chemotherapy side effects can alert
nuanced emotional responses and personal experiences oncologists of early signs of neutropenia, enabling timely
of patients. For instance, coping with an advanced cancer clinical intervention. AI-powered tools also play a critical
diagnosis involves significant emotional stress, which role in tele-oncology by enhancing communication
cannot be fully alleviated by AI chatbots. Human mental between patients and providers. In rural areas, AI-driven
health professionals, such as psychologists or oncologists, systems assist telemedicine by triaging symptoms and
are essential in assessing individual emotional needs and ensuring relevant data reaches the oncologists during
providing personalized, empathetic care, ensuring patients remote consultations. The integration of AI in oncology
receive the support they need in complex, emotionally should be viewed as a supportive tool rather than a
charged situations. replacement for human decision-making. AI’s role involves
analyzing complex data – such as imaging, genomics,
5.2. Integrating AI into clinical workflows for
optimal patient care and trends – to provide evidence-based insights, while
clinicians retain responsibility for interpreting those
While human oversight remains essential in oncology, insights, offering emotional support, tailoring decisions to
AI technologies offer significant benefits by streamlining individual patient needs, and managing nuanced clinical
clinical workflows, enhancing decision-making, and cases.
reducing administrative burdens on healthcare providers.
Thoughtful integration of AI allows clinicians to focus 5.3. Future considerations for the balance between
on high-value, complex interactions with patients, while technology and human care
AI handles repetitive or data-intensive tasks. AI-powered To ensure the sustainable, effective, and ethical integration
decision support systems can analyze large datasets and of AI in oncology care, several key strategies need to be
provide evidence-based treatment recommendations, but implemented. First, training and AI literacy for clinicians
these require clinician validation to ensure their appropriate are essential, ensuring healthcare providers can interpret
application. For instance, AI models predicting radiation AI insights and work effectively with AI tools. This
therapy outcomes by analyzing imaging and patient approach empowers clinicians to leverage AI’s benefits
history offer valuable insights, yet human oncologists must while maintaining clinical oversight, preventing the
review and confirm these recommendations to ensure they reliance on AI to replace critical human judgment. Second,
align with clinical guidelines and patient-specific needs. establishing ethical guidelines and governance structures
AI tools can also automate administrative tasks, including is vital to ensure transparency, fairness, and accountability,
appointment scheduling, data entry, and reminders, addressing potential biases that could impact patient
increasing the availability of clinical staff to concentrate care. Third, hybrid models combining AI’s computational
on direct patient care. For example, AI-driven systems that efficiency with clinicians’ nuanced judgment should be

Volume 9 Issue 1 (2025) 128 doi: 10.36922/ejmo.6251