Intelligent Auxiliary System for Chronic Disease Prevention and Treatment Based on Information Technology and Its application in Improving Patients' Trust Predicament
DOI:
https://doi.org/10.65455/aair5615关键词:
AI+Healthcare, Information Technology, Prevention & Treatment for Chronic Diseases, Intelligent Auxiliary System, Doctor-Patient Relationship摘要
Along with the rapid development of information technology, there are unprecedented opportunities and challenges in the area of chronic diseases. Chronic diseases' long-term nature, complexity and impact on patients' quality of life make it clear that traditional prevention model can not meet patients' diverse needs and increase their trust. It aims at providing personalized and accurate prevention and treatment plans based on AI, Big Data, Internet of Things, and other advanced technologies in order to improve doctor-patient trust. In this paper, we deeply discuss the system's overall structure, design, main functions, and its application effect on patients' trust dilemma.
参考
[1]VANI S M, SUDHAKAR V R, MAHENDAR A, et al. Personalized health monitoring using explainable AI: bridging trust in predictive healthcare. Scientific Reports, 2025, 15(1): 31892.
[2]SAINI B, SINGH D, SHARMA C K, et al. AI-enhanced telemedicine: transforming resource allocation and cost-efficiency analysis via advanced queueing model. Scientific Reports, 2025, 15(1): 31551.
[3]SI J. Exploring AI literacy, attitudes toward AI, and intentions to use AI in clinical contexts among healthcare students in Korea: a cross-sectional study. BMC Medical Education, 2025, 25(1): 1233.
[4]ALSUBAI S, KAROVIČ V, ALMADHOR A, et al. Future-Proofing AI Models in IoMT Environment: Adversarial Dataset Generation and Defense Strategies. Digital Twins and Applications, 2025, 2(1): e70010.
[5]MASALONIS A, NELSON C, JONES R L, et al. Trust, Security, and Regulatory Compliance in AI: Literature and Practical Experience, and the Way Forward for AI in Healthcare. Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care, 2025, 14(1): 1-5.
[6]NURITTIN A, RASIT D. Artificial Intelligence in Healthcare: Current Regulatory Landscape and Future Directions. British Journal of Hospital Medicine, 2025, 86(8): 1-21.
[7]THALDAR D, BOTTOMLEY D. Public trust of AI in healthcare in South Africa: results of a survey. BMC Medical Ethics, 2025, 26(1): 113.
[8]BELLINI V, CALABRÒ F, BIGNAMI E, et al. Applying the Model for Assessing the Value of AI (MAS-AI) Framework To Organizational AI: A Case Study of Surgical Scheduling Assessment in Italy. Journal of Medical Systems, 2025, 49(1): 108.
[9]KIRCH M N, HEBENSTREIT K, SAMWALD M. Medical triage as an AI ethics benchmark. Scientific Reports, 2025, 15(1): 30974.
[10]DAI Q, LI M, SHI S, et al. Structural equation modeling for influencing factors on behavioral intention to adopt medical AI among Chinese nurses: a nationwide cross-sectional study. BMC Nursing, 2025, 24(1): 1084.
[11]MGBAACHI L C, NGENE P E, NNAJI C U, et al. Knowledge, Attitude and Utilization of Artificial Intelligence in Healthcare among Medical Doctors at a State University Teaching Hospital in Enugu State, Nigeria. International Journal of Tropical Disease & Health, 2025, 46(8): 26-40.
[12]SONG Z, KWON T, LEE J, et al. AI-Driven Defecation Analysis by Smart Healthcare Toilet: Exploring Biometric Patterns and Eu-Tenesmus. Advanced Science, 2025, 12(30): 71162.
[13]ALONSO M, ASTOBIZA M A, LOZANO O R. AI-mediated healthcare and trust. A trust-construct and trust-factor framework for empirical research. Artificial Intelligence Review, 2025, 58(11): 337.
[14]REYNOLDS J D, MOUNTAIN S, BARTLE V, et al. Targeting everyday decision makers in research: early career researcher and patient and public involvement and engagement collaboration in an AI-in-healthcare project. Research Involvement and Engagement, 2025, 11(1): 100.
[15]NUNES S D, DAVID F P J, FILHO D S J J, et al. Comparative Evaluation of Multiplatform AI Performance on Practical Ophthalmology Exam Questions: Insights from the Brazilian Council of Ophthalmology Exam. Journal of Advances in Medicine and Medical Research, 2025, 37(8): 159-170.
