Page 126 - EJMO-9-1

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

or medication side effects, especially between clinical identifying tumors or classifying abnormalities
visits. AI-powered chatbots provide instant, evidence- in radiology scans. For example, CNNs have
based answers, and personalized recommendations. Chen demonstrated success in detecting breast cancer,
et al. reported increased patient satisfaction and reduced skin cancer, and lung cancer from radiographic
9
symptom escalation when such tools were used for real- images with accuracy comparable to or better than
time query handling. 9 human radiologists. 10,15
The persistent gaps in traditional oncology care (v) AI-powered virtual assistants and chatbots are
systems, including limited patient engagement, geographic interactive software applications that use AI,
disparities, and resource constraints, form the foundation including NLP and ML, to simulate conversation
for this study. AI-powered virtual assistants and chatbots and provide information to users. In oncology,
offer an innovative, scalable, and empathetic approach to these systems support patients by answering
addressing these challenges. questions about symptoms, treatment schedules,
medication side effects, and emotional well-being.
1.4. Explanation of key technical terms and concepts They offer 24/7 support, bridge gaps in patient
care, and improve access to oncology information,
To ensure clarity for readers who are unfamiliar with particularly for patients in remote or underserved
technical terms and concepts, the following definitions are areas. 5,16
provided in the context of oncology: (vi) Telemedicine integration involves the remote
(i) NLP is a branch of AI focused on enabling
machines to understand, interpret, and generate delivery of healthcare services and information
human language. In oncology, NLP is used to through telecommunications technology, such as
process patient inputs or medical records, deriving video consultations or text-based communication.
meaningful insights. For instance, NLP can power AI-powered virtual assistants and chatbots
AI-powered chatbots to understand patient queries can integrate telemedicine features, allowing
related to symptoms or treatment schedules and patients to access virtual consultations, schedule
appointments, and receive medical advice remotely.
provide accurate, timely responses. It can also This expands access to expert care, especially for
analyze unstructured clinical notes to identify rural or underserved populations. 12
trends, patient concerns, or potential risks. 6
(ii) ML, a subset of AI, allows systems to learn patterns (vii) Deep learning is a subset of ML that uses artificial
and make decisions based on data without being neural networks with many layers (hence “deep”) to
explicitly programmed. In oncology, ML algorithms recognize patterns in large and complex datasets.
are employed to analyze large datasets for pattern In oncology, deep learning models are applied
recognition, such as predicting disease progression, to tasks such as medical image analysis (e.g.,
assessing chemotherapy responses, or improving magnetic resonance imaging [MRI] or computed
diagnostic accuracy. ML processes imaging data, tomography [CT] scans for tumor detection),
genomic profiles, and patient histories to uncover predicting treatment responses, and analyzing
insights that assist clinicians in personalized genomic sequences to uncover biomarkers or
mutations related to cancer development.
14,17
treatment planning. 9
(iii) CRISPR is a genome-editing tool that allows This article explores the growing role of AI-powered
precise modification of DNA, enabling researchers chatbots in oncology, with a particular focus on their
to alter genetic information with high accuracy. In potential to enhance cancer treatment. The discussion
oncology, CRISPR has been used to edit immune delves into how AI chatbots, such as RITA, are being
cells, such as T-cells, making them more effective in utilized to provide patients with accessible and reliable
targeting cancer cells. It holds promise for creating information, support their emotional well-being, and
innovative cancer therapies by modifying genes improve overall patient care by reducing the strain
linked to tumor growth or resistance mechanisms, on healthcare professionals. In addition, the article
and it is currently explored in clinical trials for its highlights the future applications of AI-driven chatbots
potential to revolutionize cancer treatment. 8,13 in oncology, offering insights into their capacity to
(iv) Convolutional neural networks (CNNs) are a type personalize treatment plans, streamline communication,
of deep learning model inspired by the human and improve treatment outcomes. The aim is to provide
visual system, designed to process visual imagery a comprehensive overview of how AI chatbots can play a
and detect patterns in images. In oncology, CNNs pivotal role in transforming oncology care. The article is
are used in medical imaging analysis, such as structured as follows: Section 2 presents a literature survey,

Volume 9 Issue 1 (2025) 118 doi: 10.36922/ejmo.6251