Main Article Content

Wajiha Zafar1, Danish Khilani2, Hina Abbasi3, Giuseppe Giorgianni4, Dr. Nabila Noble5, Dr. Bency Babu6, Dr. Fidha Hussain7, Abdur Rehman8


Patient Experience; Health Care; Artificial Intelligence


The primary objective of this research is to investigate the impact of artificial intelligence (AI) on the patient experience within healthcare services.

Methods: This study employs an integrative approach, drawing from modern institutional frameworks to explore the influence of AI on patient interactions within healthcare settings. Data were sourced from documents, utilizing databases such as LILACS and Medline to identify relevant healthcare literature. Five articles were selected from the gathered samples to illustrate the significance of adopting new technologies in enhancing patient experiences.

Results: The analysis highlights the importance of AI in transforming traditional healthcare management techniques, leading to improved patient safety and quality of care. Despite the limited number of studies on this topic, the selected articles underscore the potential benefits of incorporating AI-driven solutions in healthcare practices.

Abstract 157 | PDF Downloads 36


1. Aklilu, J. G., Sun, M. W., Goel, S., Bartoletti, S., Rau, A., Olsen, G., . . . Milstein, A. (2024). Artificial Intelligence Identifies Factors Associated with Blood Loss and Surgical Experience in Cholecystectomy. NEJM AI, 1(2), AIoa2300088.
2. Ashayeri, H., Jafarizadeh, A., Yousefi, M., Farhadi, F., & Javadzadeh, A. (2024). Retinal imaging and Alzheimer’s disease: a future powered by Artificial Intelligence. Graefe's Archive for Clinical and Experimental Ophthalmology, 1-13.
3. Bansal, H., Gupta, D., & Anand, D. (2024). Blockchain and Artificial Intelligence in Telemedicine and Remote Patient Monitoring. Handbook on Augmenting Telehealth Services, 279-294.
4. Baumgart, D. C. (2024). An intriguing vision for transatlantic collaborative health data use and artificial intelligence development. NPJ Digital Medicine, 7(1), 19.
5. Bereska, J. I., Janssen, B. V., Nio, C. Y., Kop, M. P., Kazemier, G., Busch, O. R., . . . Besselink, M. G. (2024). Artificial intelligence is used to assess vascular involvement and tumour resectability on CT in patients with pancreatic cancer. European Radiology Experimental, 8(1), 18.
6. Bordukova, M., Makarov, N., Rodriguez-Esteban, R., Schmich, F., & Menden, M. P. (2024). Generative artificial intelligence empowers digital twins in drug discovery and clinical trials. Expert Opinion on Drug Discovery, 19(1), 33-42.
7. Bumm, R., Zaffino, P., Lasso, A., Estépar, R. S. J., Pieper, S., Wasserthal, J., . . . Wäckerlin, A. (2024). Artificial intelligence (AI)-assisted chest computer tomography (CT) insights: a study on intensive care unit (ICU) admittance trends in 78 coronavirus disease 2019 (COVID-19) patients. Journal of Thoracic Disease, 16(2).
8. Choudhary, A., Gopalakrishnan, N., Joshi, A., Balakrishnan, D., Chhablani, J., Yadav, N. K., . . . Shetty, R. (2024). Recommendations for diabetic macular oedema management by retina specialists and large language model-based artificial intelligence platforms. International Journal of Retina and Vitreous, 10(1), 22.
9. Constable, M. D., Shum, H. P., & Clark, S. (2024). Enhancing surgical performance in cardiothoracic surgery with innovations from computer vision and artificial intelligence: a narrative review. Journal of Cardiothoracic Surgery, 19(1), 94.
10. El-Tallawy, S. N., Pergolizzi, J. V., Vasiliu-Feltes, I., Ahmed, R. S., LeQuang, J. K., El-Tallawy, H. N., . . . Naguib, M. S. (2024). Incorporation of “Artificial Intelligence” for Objective Pain Assessment: A Comprehensive Review. Pain and Therapy, 1-25.
11. Eswaran, U., & Khang, A. (2024). Artificial Intelligence (AI)-Aided Computer Vision (CV) in Healthcare Systems Computer Vision and AI-Integrated IoT Technologies in the Medical Ecosystem (pp. 125-137): CRC Press.
12. Feinstein, M., Katz, D., Demaria, S., & Hofer, I. S. (2024). Remote monitoring and artificial intelligence: outlook for 2050. Anesthesia & Analgesia, 138(2), 350-357.
13. Gabrani, G., Gupta, S., Vyas, S., & Arya, P. (2024). Revolutionizing Healthcare: Impact of Artificial Intelligence in Disease Diagnosis, Treatment, and Patient Care Handbook on Augmenting Telehealth Services (pp. 17-31): CRC Press.
14. Gupta, S., Vanteru, M. K., Angadi, S., Manikandan, K., Tiwari, M., & Dhanraj, J. A. (2024). Current Breakthroughs and Future Perspectives in Surgery Based on AI-Based Computing Vision. Human Cancer Diagnosis and Detection Using Exascale Computing, 227, 227.
15. Jacob, A. M., Sneed, K., & Pathak, Y. (2024). A Possibility of Application of Human Cognitive Psychology to Artificial Intelligence to Improve Dermatological Diagnostics and its Accuracy. Nur Primary Care, 8(1), 1-6.
16. Jawaid, S. A. Era of Artificial Intelligence and Its Implementation in Controlling Side Effects during Healthcare Practices.
17. Knudsen, J. E., Ghaffar, U., Ma, R., & Hung, A. J. (2024). Clinical applications of artificial intelligence in robotic surgery. Journal of Robotic Surgery, 18(1), 102.
18. Lysen, F., & Wyatt, S. (2024). Refusing participation: hesitations about designing responsible patient engagement with artificial intelligence in healthcare. Journal of Responsible Innovation, 11(1), 2300161.
19. Lysø, E. H., Hesjedal, M. B., Skolbekken, J.-A., & Solbjør, M. (2024). Men's sociotechnical imaginaries of artificial intelligence for prostate cancer diagnostics–A focus group study. Social Science & Medicine, 116771.
20. Marco-Ruiz, L., Hernandez, M. A. T., Ngo, P. D., Makhlysheva, A., Svenning, T. O., Dyb, K., . . . Tayefi, M. (2024). A multinational study on artificial intelligence adoption: Clinical implementers' perspectives. International Journal of Medical Informatics, 105377.
21. Martelli, E., Capoccia, L., Di Francesco, M., Cavallo, E., Pezzulla, M. G., Giudice, G., . . . Panagrosso, M. (2024). Current Applications and Future Perspectives of Artificial Intelligence in Vascular Surgery and Peripheral Artery Disease.
22. Mese, I. (2024). Leveraging virtual reality-augmented reality technologies to complement artificial intelligence-driven healthcare: the future of patient–doctor consultations. European Journal of Cardiovascular Nursing, 23(1), e9-e10.
23. Mika, S., Gola, W., Gil-Mika, M., Wilk, M., & Misiolłek, H. (2024). Ultrasonographic Applications of Novel Technologies and Artificial Intelligence in Critically Ill Patients. Journal of Personalized Medicine, 14(3), 286.
24. Mira, E. S., Sapri, A. M. S., Aljehanı, R. F., Jambı, B. S., Bashir, T., El-Kenawy, E.-S. M., & Saber, M. (2024). Early Diagnosis of Oral Cancer Using Image Processing and Artificial Intelligence. Fusion: Practice and Applications, 14(1), 293-308.
25. Nikolić, M., Stanimirović, A., & Stoimenov, L. (2024). Visual Programming Support for the Explainable Artificial Intelligence. Paper presented at the Conference on Information Technology and its Applications.
26. Papadopoulou, S.-L., Dionysopoulos, D., Mentesidou, V., Loga, K., Michalopoulou, S., Koukoutzeli, C., . . . Styliadis, I. (2024). Artificial Intelligence-assisted evaluation of cardiac function by oncology staff in chemotherapy patients. European Heart Journal-Digital Health, ztae017.
27. Qureshi, J., & Khan, S. (2024). Artificial Intelligence (AI) Deepfakes in Healthcare Systems: A Double-Edged Sword? Balancing Opportunities and Navigating Risks.
28. Ramírez, J. G. C., & Islam, M. M. (2024). Utilizing Artificial Intelligence in Real-World Applications. Journal of Artificial Intelligence General Science (JAIGS) ISSN: 3006-4023, 2(1), 14-19.
29. Reza, T., & Bokhari, S. F. H. (2024). Partnering With Technology: Advancing Laparoscopy With Artificial Intelligence and Machine Learning. Cureus, 16(3).
30. Rogalla, P., Cadour, F., & Kim, T. K. (2024). Pancreatic Adenocarcinoma Resectability Assessment: Could a Visual Aid Tool Save Patients and Radiology Residents? (pp. 08465371241230905): SAGE Publications Sage CA: Los Angeles, CA.
31. Rony, M. K. K., Kayesh, I., Bala, S. D., Akter, F., & Parvin, M. R. (2024). Artificial intelligence in future nursing care: Exploring nursing professionals' perspectives- A descriptive qualitative study. Heliyon.
32. Sardesai, N., Russo, P., Martin, J., & Sardesai, A. (2024). Utilizing generative conversational artificial intelligence to create simulated patient encounters, a pilot study for anaesthesia training. Postgraduate Medical Journal, qgad137.
33. Shafik, W., Hidayatullah, A. F., Kalinaki, K., & Aslam, M. M. (2024). Artificial Intelligence (AI)-Assisted Computer Vision (CV) in Healthcare Systems Computer Vision and AI-Integrated IoT Technologies in the Medical Ecosystem (pp. 17-36): CRC Press.
34. Sharma, K. (2024). Personalized Telemedicine Utilizing Artificial Intelligence, Robotics, and Internet of Medical Things (IOMT) Handbook of Research on Artificial Intelligence and Soft Computing Techniques in Personalized Healthcare Services (pp. 301-323): Apple Academic Press.
35. Sharmila Nirojini, P., Kanaga, K., Devika, S., & Pradeep, P. (2024). Exploring the Impact of Artificial Intelligence on Patient Care: A Comprehensive Review of Healthcare Advancements. Sch Acad J Pharm, 2, 67-81.
36. Skorburg, J. A., O'Doherty, K., & Friesen, P. (2024). Persons or data points? Ethics, artificial intelligence, and the participatory turn in mental health research. American Psychologist, 79(1), 137.
38. Tan, T. F., Elangovan, K., Jin, L., Jie, Y., Yong, L., Lim, J., . . . Ke, Y. (2024). Fine-tuning Large Language Model (LLM) Artificial Intelligence Chatbots in Ophthalmology and LLM-based evaluation using GPT-4. arXiv preprint arXiv:2402.10083.
39. Uchikov, P., Khalid, U., Kraev, K., Hristov, B., Kraeva, M., Tenchev, T., . . . Taneva, D. (2024). Artificial Intelligence in the Diagnosis of Colorectal Cancer: A Literature Review. Diagnostics, 14(5), 528.
40. Wenderott, K., Krups, J., Luetkens, J. A., & Weigl, M. (2024). Radiologists’ perspectives on the workflow integration of an artificial intelligence-based computer-aided detection system: A qualitative study. Applied Ergonomics, 117, 104243.
41. Wimpfheimer, O., & Kimmel, Y. (2024). Artificial Intelligence in Medical Imaging: An Overview of a Decade of Experience. The Israel Medical Association Journal: IMAJ, 26(2), 122-125.
42. Wong, D. C., & Williams, S. (2024). Artificial intelligence analysis of videos to augment clinical assessment: an overview. Neural Regeneration Research, 19(4), 717-718.
43. Yilma, B. A., Kim, C. M., Cupchik, G. C., & Leiva, L. A. (2024). Artful Path to Healing: Using Machine Learning for Visual Art Recommendation to Prevent and Reduce Post-Intensive Care. arXiv preprint arXiv:2402.15643.
44. Zhang, S., Cui, W., Wu, Y., & Ji, M. (2024). Description of an individualized delirium intervention in intensive care units for critically ill patients delivered by an artificial intelligence-assisted system: using the TIDieR checklist. Journal of Research in Nursing, 17449871231219124.