Page 129 - EJMO-9-1

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

Table 1. (Continued)
Author/s Invention/ Technology Impact Merits Demerits Future
Technology used enhancement
Shen et al. 20 AI in blood Neural Detection of Faster diagnosis Inaccuracies with Real-time AI
cancer diagnosis Networks, leukemia and and treatment complex blood for personalized
machine lymphoma decisions tests hematological
learning monitoring
Hwang et al. 21 AI for skin cancer Convolutional Classification of Improved Needs Automation in
histopathology networks skin cancer types diagnostic high-quality large-scale screening
in images consistency histopathology for skin cancer
data
Liu et al. 22 AI for brain Machine Early detection of Faster and more Lack of Combining AI with
tumor diagnosis learning brain tumors accurate tumor large-scale surgical robotics for
detection validated datasets enhanced treatment
precision
Choi et al. 23 AI in cancer Machine Interpreting cancer Personalized Complexity of Integrating
genomic data learning genomic data for treatment genomic data multi-omics data for
analysis therapy recommendations interpretation broader insights
Tan et al. 24 AI in pancreatic Deep learning, Improved early High early Difficulty with AI-driven early
cancer detection CNN detection of diagnosis rate imaging quality detection in
pancreatic cancer and variety screening programs
Zhang et al. 25 AI in cancer drug Deep learning, Accelerating drug Faster Limited by Improved integration
discovery machine discovery for identification of databases and with patient-specific
learning cancer promising drug accuracy data for personalized
candidates drugs
Abbreviations: AI: Artificial intelligence; CNN: Convolutional neural network.

3. AI virtual assistants and chatbots: symptom control through chatbot-assisted care. In
6,20
Transforming patient support in oncology addition, AI tools provide 24/7 emotional support, helping
reduce stress and improve overall well-being for patients
3.1. Problem identification undergoing cancer treatment. Finally, AI-driven chatbots
23
AI has the potential to transform oncology by improving help improve treatment adherence by sending medication
early detection, treatment planning, patient monitoring, reminders and follow-up prompts, leading to a 20%
drug discovery, and enhancing the overall patient increase in adherence rates. Overall, these advancements
17
experience. Its ability to provide continuous, real-time demonstrate AI’s ability to enhance patient engagement,
support ensures that patients have instant access to crucial ensure timely access to care, and support improved clinical
medical information, facilitating a more personalized outcomes in oncology.
approach to care. AI-powered chatbots address several key
challenges in oncology, supported by evidence from recent 3.2. Block diagram modules for oncology chatbots–AI
studies. First, AI chatbots bridge geographic gaps in care The proposed block diagram for oncology-specific AI
delivery, especially for patients in underserved and remote chatbots integrates key components informed by literature
areas. Research shows that these tools enhance access to and the authors’ expertise in AI-driven healthcare tools.
timely and accurate medical information, ensuring that The framework aims to enhance patient care in oncology by
specialized care is not delayed due to location. 12,20 Second, addressing the unique challenges of cancer treatment while
AI-driven virtual assistants improve patient engagement by incorporating existing best practices in AI applications.
using NLP to interact with patients conversationally. These
interactions help address the emotional burden associated 3.2.1. Patient interaction module
with cancer treatment, providing timely guidance and The patient interaction module facilitates patient input,
reducing anxiety. 23,25 such as symptom descriptions or inquiries, serving as the
Moreover, AI chatbots offer real-time, evidence-based foundation for chatbot interactions. AI-powered chatbots,
symptom management, such as addressing chemotherapy- such as RITA, have demonstrated the effectiveness of
induced nausea or fatigue. Studies have demonstrated 24/7 patient interaction systems, by improving engagement
significant improvements in patient satisfaction and and reducing the burden on healthcare providers.

Volume 9 Issue 1 (2025) 121 doi: 10.36922/ejmo.6251