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


Erul E., Aktekin Y., Danışman F. B., Gümüştaş Ş. A., Aktekin B. S., YEKEDÜZ E., ...Daha Fazla

Cancer Control, cilt.32, 2025 (SCI-Expanded, Scopus) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 32
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1177/10732748251343245
  • Dergi Adı: Cancer Control
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, CINAHL, EMBASE, MEDLINE, Directory of Open Access Journals
  • Anahtar Kelimeler: artificial intelligence, cancer care, chatbots, comfort levels, healthcare concerns, machine learning and deep learning systems, natural language processing, patient perspectives
  • Ankara Üniversitesi Adresli: Evet

Özet

Introduction: The 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 Methods: This 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. Results: A 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. Conclusions: Patients’ 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.