Perceptions, Attitudes, and Concerns on Artificial Intelligence Applications in Patients with Cancer

Abstract

IntroductionThe use of artificial intelligence (AI) in oncology has increased rapidly, transforming various healthcare areas such as pathology, radiology, diagnostics, prognosis, genomics, treatment planning, and clinical trials. However, perspectives, comfort levels, and concerns about AI in cancer care remain largely unexplored.Materials and MethodsThis prospective, descriptive cross-sectional survey study was conducted between May 20, 2024 and October 22, 2024, among 363 patients with cancer from two different hospitals affiliated with Ankara University, a tertiary care center in Türkiye. The survey included three distinct sections: (1) Perceptions: Patients' general views on AI's impact in oncology; (2) Attitudes: Comfort level with AI performing medical tasks; (3) Concerns: Specific fears related to AI implementation (eg, diagnostic errors, data privacy, healthcare costs). Survey responses were summarized descriptively, and differences by age, gender, and education were analyzed using chi-square tests.ResultsA majority (50.7%) believed AI would somewhat (32%) or significantly (18.7%) improve healthcare. However, one-third of patients (33.1%) were very uncomfortable with AI diagnosing cancer, with higher discomfort among less-educated participants (P < .005). Top patient concerns included AI making incorrect diagnoses (31.1%), increasing healthcare costs (27.5%), and not keeping data private (19.6%). Patients with higher education levels expressed less discomfort and fewer concerns.ConclusionsPatients' perceptions and attitudes on AI varied significantly based on education, highlighting the need for targeted educational initiatives. While AI holds potential to revolutionize cancer care, addressing concerns about accuracy, security, and transparency is critical to enhance its acceptance and effectiveness in clinical practice.

Keywords: artificial intelligence; cancer care; chatbots; comfort levels; healthcare concerns; machine learning and deep learning systems; natural language processing; patient perspectives.

Figure 1.

Illustrates the Three Distinct Measurement Scales Used in the Survey. The Perception Scale Assesses Patients’ General Views on AI’s Impact in Oncology, the Comfort Scale Evaluates Their Emotional Response and Willingness to Accept AI in Clinical Practice, and the Concern Scale Measures Specific Fears Related to AI Adoption, Such as Misdiagnosis and Privacy Issues.

Figure 2.

Proportions of the Answers for 90% and 98% Model Accuracy.

Figure 3.

Illustrates the Concerns of Cancer Patients Regarding the Use of Artificial Intelligence in Cancer Care.

Figure 4.

Correlation Matrix Illustrating the Relationships Between Perception, Comfort, and Concern Scores Among Oncology Patients.

Figure 5.

Using Our Causal Graph, we Estimate a Linear Regression Model to Examine the Effects of Education to Comforts and Concerns of AI in Healthcare by Factoring the Confounding Variables and excluding the Mediator.

Figure 6.

Within-cluster sum of squares (WCSS) for different cluster numbers.

Figure 7.

Cluster Visualization Based on Concern and Comfort Scores.

Figure 8.

Distribution of Concern-Comfort Clusters Across Education and Age Categories. (A) Cluster Proportions by Educational Background. (B) Cluster Proportions by Age Group.