Empowering health care consumers & understanding patients' perspectives on AI integration in oncology and surgery: A perspective

被引:3
作者
Awuah, Wireko Andrew [1 ]
Aderinto, Nicholas [2 ]
Poornaselvan, Jeisun [3 ]
Tan, Joecelyn Kirani [4 ]
Shah, Muhammad Hamza [5 ]
Ashinze, Patrick [6 ]
Pujari, Anushka G. [7 ]
Bharadwaj, Hareesha Rishab [8 ]
Abdul-Rahman, Toufik [1 ]
Atallah, Oday [9 ]
机构
[1] Sumy State Univ, Fac Med, Sanatorna St 31, Sumy 40000, Sumy Oblast, Ukraine
[2] LAUTECH Teaching Hosp, Internal Med Dept, Ogbomosho, Nigeria
[3] Univ Coll Dublin, Sch Med, Dublin, Ireland
[4] Univ St Andrews, Fac Med, St Andrews, Scotland
[5] Queens Univ Belfast, Sch Med, Belfast, North Ireland
[6] Univ Ilorin, Fac Clin Sci, Ilorin, Nigeria
[7] Royal Coll Surgeons Ireland, Dublin, Ireland
[8] Univ Manchester, Fac Biol Med & Hlth, Manchester, England
[9] Hannover Med Sch, Dept Neurosurg, Hannover, Germany
关键词
artificial intelligence; oncology; patients perspectives; surgery; ARTIFICIAL-INTELLIGENCE;
D O I
10.1002/hsr2.2268
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
IntroductionArtificial intelligence (AI) is transforming oncology and surgery by improving diagnostics, personalizing treatments, and enhancing surgical precision. Patients appreciate AI for its potential to provide accurate prognoses and tailored therapies. However, AI's implementation raises ethical concerns, data privacy issues, and the need for transparent communication between patients and health care providers. This study aims to understand patients' perspectives on AI integration in oncology and surgery to foster a balanced and patient-centered approach.MethodsThe study utilized a comprehensive literature review and analysis of existing research on AI applications in oncology and surgery. The focus was on examining patient perceptions, ethical considerations, and the potential benefits and risks associated with AI integration. Data was collected from peer-reviewed journals, conference proceedings, and expert opinions to provide a broad understanding of the topic. The perspectives of patients was also emphasized to highlight the nuances of their acceptance and concerns regarding AI in their health care.ResultsPatients generally perceive AI in oncology and surgery as beneficial, appreciating its potential for more accurate diagnoses, personalized treatment plans, and improved surgical outcomes. They particularly value AI's role in providing timely and precise diagnostics, which can lead to better prognoses and reduced anxiety. However, concerns about data privacy, ethical implications, and the reliability of AI systems were prevalent. Consequently, trust in AI and health care providers was deemed as a crucial factor for patient acceptance. Additionally, the need for transparent communication and ethical safeguards was also highlighted to address these concerns effectively.ConclusionThe integration of AI in oncology and surgeryholds significant promise for enhancing patient care and outcomes. Patients view AI as a valuable tool that can provide accurate prognoses and personalized treatments. However, addressing ethical concerns, ensuring data privacy, and building trust through transparent communication are essential for successful AI integration. Future initiatives should focus on refining AI algorithms, establishing robust ethical guidelines, and enhancing patient education to harmonize technological advancements with patient-centered care principles. Artificial intelligence (AI) has ushered in transformative potential in surgery and oncology, including enhanced patient care through novel treatment plans and diagnosis, and improved precision. Although AI offers numerous benefits in the field of surgical oncology, it also presents several challenges, including ethical issues, safety and privacy risks, bias in algorithms, and increased health disparities due to limited access. As important as recognizing and addressing the various viewpoints of patients and their families on AI usage are, these patients' perspectives on AI in surgery and oncology have been vastly underexplored. Future initiatives should prioritize AI algorithm refinement, ethical guidelines, and robust data governance mechanisms because successful AI integration into health care necessitates a balance between technological advancement, the preservation of fundamental ethical principles, and patient-centered care.
引用
收藏
页数:5
相关论文
共 28 条
[1]   Artificial intelligence and robotics: a combination that is changing the operating room [J].
Andras, Iulia ;
Mazzone, Elio ;
van Leeuwen, Fijs W. B. ;
De Naeyer, Geert ;
van Oosterom, Matthias N. ;
Beato, Sergi ;
Buckle, Tessa ;
O'Sullivan, Shane ;
van Leeuwen, Pim J. ;
Beulens, Alexander ;
Crisan, Nicolae ;
D'Hondt, Frederiek ;
Schatteman, Peter ;
van Der Poel, Henk ;
Dell'Oglio, Paolo ;
Mottrie, Alexandre .
WORLD JOURNAL OF UROLOGY, 2020, 38 (10) :2359-2366
[2]   Deep learning for lung Cancer detection and classification [J].
Asuntha, A. ;
Srinivasan, Andy .
MULTIMEDIA TOOLS AND APPLICATIONS, 2020, 79 (11-12) :7731-7762
[3]   Radiogenomics influence on the future of prostate cancer risk stratification [J].
Banerjee, Vinayak ;
Wang, Shu ;
Drescher, Max ;
Russell, Ryan ;
Siddiqui, M. Minhaj .
THERAPEUTIC ADVANCES IN UROLOGY, 2022, 14
[4]   Impact of data on generalization of AI for surgical intelligence applications [J].
Bar, Omri ;
Neimark, Daniel ;
Zohar, Maya ;
Hager, Gregory D. ;
Girshick, Ross ;
Fried, Gerald M. ;
Wolf, Tamir ;
Asselmann, Dotan .
SCIENTIFIC REPORTS, 2020, 10 (01)
[5]  
Cobianchi L, 2023, WORLD J EMERG SURG, V18, DOI 10.1186/s13017-022-00467-3
[6]   Radiogenomics in Renal Cancer Management-Current Evidence and Future Prospects [J].
Ferro, Matteo ;
Musi, Gennaro ;
Marchioni, Michele ;
Maggi, Martina ;
Veccia, Alessandro ;
Del Giudice, Francesco ;
Barone, Biagio ;
Crocetto, Felice ;
Lasorsa, Francesco ;
Antonelli, Alessandro ;
Schips, Luigi ;
Autorino, Riccardo ;
Busetto, Gian Maria ;
Terracciano, Daniela ;
Lucarelli, Giuseppe ;
Tataru, Octavian Sabin .
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2023, 24 (05)
[7]   Prostate Cancer Radiogenomics-From Imaging to Molecular Characterization [J].
Ferro, Matteo ;
de Cobelli, Ottavio ;
Vartolomei, Mihai Dorin ;
Lucarelli, Giuseppe ;
Crocetto, Felice ;
Barone, Biagio ;
Sciarra, Alessandro ;
Del Giudice, Francesco ;
Muto, Matteo ;
Maggi, Martina ;
Carrieri, Giuseppe ;
Busetto, Gian Maria ;
Falagario, Ugo ;
Terracciano, Daniela ;
Cormio, Luigi ;
Musi, Gennaro ;
Tataru, Octavian Sabin .
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2021, 22 (18)
[8]   Attitudes of the Surgical Team Toward Artificial Intelligence in Neurosurgery: International 2-Stage Cross-Sectional Survey [J].
Horsfall, Hugo Layard ;
Palmisciano, Paolo ;
Khan, Danyal Z. ;
Muirhead, William ;
Koh, Chan Hee ;
Stoyanov, Danail ;
Marcus, Hani J. .
WORLD NEUROSURGERY, 2021, 146 :E724-E730
[9]   How do patients perceive the AI-radiologists interaction? Results of a survey on 2119 responders [J].
Ibba, Simona ;
Tancredi, Chiara ;
Fantesini, Arianna ;
Cellina, Michaela ;
Presta, Roberta ;
Montanari, Roberto ;
Papa, Sergio ;
All, Marco .
EUROPEAN JOURNAL OF RADIOLOGY, 2023, 165
[10]   The Impact of Artificial Intelligence on Health Equity in Oncology: Scoping Review [J].
Istasy, Paul ;
Lee, Wen Shen ;
Iansavichene, Alla ;
Upshur, Ross ;
Gyawali, Bishal ;
Burkell, Jacquelyn ;
Sadikovic, Bekim ;
Lazo-Langner, Alejandro ;
Chin-Yee, Benjamin .
JOURNAL OF MEDICAL INTERNET RESEARCH, 2022, 24 (11)