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Perception and Awareness of Artificial Intelligence in Cancer Research, Early Detection, and Prevention: A Statistical Study

Students & Supervisors

Student Authors
Ahmad Zubayer Mostafa
Md Wahiduzzaman Nejhum
Bachelor of Science in Computer Science & Engineering, FST
Naveed Ahmed
Bachelor of Science in Computer Science & Engineering, FST
Afnan Hossain
Supervisors
Md. Mortuza Ahmmed
Associate Professor, Faculty, FST

Abstract

Background: Artificial Intelligence (AI) is rapidly reshaping the field of cancer research, revolutionizing early detection, prevention strategies, and personalized treatment planning. AI models can review symptoms, flag potential cancer risks and analyze medical images like X-rays, CT scans, and MRIs with high precision, enabling early detection of subtle abnormalities, enhancing speed and accuracy, and assisting patients and doctors throughout the diagnostic process. Despite these technological breakthroughs, the true impact of AI in cancer care depends not only on its performance but also on societal acceptance. Public perception, trust in AI systems, understanding of their capabilities and limitations, and concerns around ethical issues—such as data privacy, algorithmic transparency, and the importance of collaboration between human expertise and AI— play a crucial role in determining the pace and extent of AI integration in clinical settings. Methods: The study was conducted using primary data collected through online surveys and community discussions. A structured questionnaire was distributed to participants from diverse backgrounds and age groups, with data collected over five months from March to July 2025, enabling responses from a varied participant pool. A total of 222 online responses were recorded. The analysis was structured around four key areas: • Awareness and Exposure to AI • Acceptance and Public Readiness • Trust and Ethical Considerations • Data Security and Privacy Concerns Descriptive statistical methods were applied to analyze the survey data, highlighting trends and response distributions. Data visualizations were performed using statistical tools such as SPSS and Tableau. No individual clinical evaluations were conducted, the study relied solely on self-reported and aggregated survey data to derive insights. Results: In terms of awareness, 63.5% of participants—especially younger ones—had encountered AI in disease detection and believed it could improve diagnostic accuracy and speed. Regarding trust and ethics, 53.8% expressed more concern about AI errors than confidence in its success, with 63.5% favoring human oversight in diagnoses. For acceptance, 71.2% showed interest in AI health assistants if they enhanced accessibility and lowered costs, highlighting the need for awareness campaigns and regulation to build trust. Privacy remained a major concern, as 55.8% were reluctant to share medical data due to fears of misuse, breaches, and lack of informed consent. Conclusion: While the majority of participants demonstrated readiness to embrace AI-driven cancer detection and care, trust remains conditional on transparency, ethical safeguards, and clear regulatory frameworks. Educating the public, improving AI accuracy, and ensuring secure data handling practices are essential to increasing public willingness. As AI continues to advance in healthcare, addressing these concerns will be critical for its widespread adoption and ethical integration into medical systems.

Keywords

Keywords: Artificial Intelligence (AI) Machine Learning (ML) Oncology Medical Imaging Genetic profiling Public perception.

Publication Details

  • Type of Publication: Conference 
  • Conference Name: 1st National BioMed Health ResearchCon 2025
  • Date of Conference: 28/08/2025 - 28/08/2025
  • Venue: Dr. Milon Auditorium, Dhaka Medical College
  • Organizer: Dhaka Medical College Research and Academic Club
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