Page 125 - EJMO-9-1

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

treatment options. This use of AI in oncology represents key components of oncology-specific AI chatbot systems.
a promising advancement that enhances accessibility and The proposed framework integrates state-of-the-art AI
reduces strain on clinical resources, ultimately improving technologies while addressing practical considerations,
the overall quality of care. 16,17 such as patient support, adherence monitoring, and data
security.
1.1. Study objectives
This study aims to explore the transformative potential of 1.2.4. Interpretation and validation
AI-powered virtual assistants and chatbots in oncology The proposed framework and insights were contextualized
care. The primary objectives are: through the authors’ professional experience in AI-driven
• To evaluate the impact of AI chatbots on improving healthcare solutions. To validate the conceptual model and
patient engagement, emotional support, and treatment demonstrate its potential effectiveness, comparisons were
adherence in oncology. made with existing AI chatbot systems, such as RITA.
• To identify the key technological components, such The purpose of this paper is to explore the role of
as natural language processing (NLP) and ML, that AI-powered virtual assistants and chatbots in transforming
drives the effectiveness of these systems.
• To assess the benefits and challenges of implementing oncology care by addressing unmet needs and improving
AI chatbots in clinical oncology settings, particularly patient outcomes. While current oncology care has seen
in underserved or remote areas. tremendous advances, several critical gaps remain, that
• To propose a conceptual framework for developing hinder optimal patient support, especially in areas, such
as accessibility, emotional well-being, and treatment
oncology-specific AI chatbot systems, incorporating
best practices and addressing identified challenges. adherence. This paper seeks to evaluate how AI-powered
tools can bridge these gaps by offering continuous, real-
1.2. Methodology description time, and personalized patient support.
The study employed a multi-step methodology to achieve 1.3. Identified gaps in cancer care: Opportunities for
the stated objectives. AI chatbots
1.2.1. Literature review Cancer care faces several critical challenges that can be
addressed through the innovative use of AI-powered
A comprehensive search strategy was employed, targeting
databases such as PubMed, IEEE Xplore, and Scopus with chatbots. Accessibility to specialized oncology care remains
a significant issue for patients in underserved and rural
keywords such as “AI chatbots,” “oncology care,” “patient areas, often leading to delays or missed opportunities for
support,” and “NLP in healthcare.” The inclusion criteria
focused on peer-reviewed articles published between 2015 early intervention. AI chatbots bridge this gap by providing
and 2023 that discussed AI applications in oncology care, with timely and accurate information, remote support, and
only English-language studies considered. Articles that were real-time medical advice, as highlighted by Wang and
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non-peer-reviewed, lacked robust methodologies, or did not Li, particularly in low-resource settings. In addition, the
directly pertain to oncology or AI chatbots were excluded. emotional toll of cancer often overwhelms both patients
Key information, including the type of AI technology used, and their families, with traditional care models unable to
patient outcomes, and implementation challenges, were offer immediate psychological relief. AI chatbots provide
extracted and systematically tabulated for analysis. empathy, reassurance, and coping strategies in a 24/7,
non-judgmental environment. For instance, the RITA
1.2.2. Synthesis of findings chatbot from Velindre University NHS Trust has effectively
The findings were synthesized to uncover recurring alleviated patient stress through real-time emotional
5,16
themes, such as the technological capabilities of AI support.
chatbots, their applications in oncology, and challenges, Another significant challenge in oncology care is
such as data privacy and system accuracy. Both quantitative non-adherence to complex treatment regimens, which
and qualitative trends were analyzed, with comparisons undermines care outcomes. AI chatbots tackle this issue by
drawn from the surveyed studies to identify gaps and sending proactive reminders and delivering personalized
opportunities in the field. information to encourage adherence. Research by Lee
et al. demonstrated a 20% improvement in medication
17
1.2.3. Development of a conceptual framework adherence when AI-driven reminders were integrated
7
Drawing from the literature review and the authors’ into patient care. Furthermore, cancer patients frequently
expertise, a block diagram was developed to illustrate the need immediate responses to questions about symptoms

Volume 9 Issue 1 (2025) 117 doi: 10.36922/ejmo.6251