Keywords
medical imaging
efficiency
interpretation
diagnosis
How to Cite
Abstract
Medical imaging plays a crucial role in the diagnosis and treatment of various medical conditions. However, the interpretation of medical images can be time-consuming and error-prone, leading to delays in patient care and potentially compromising outcomes. Artificial intelligence (AI) has emerged as a promising technology to enhance medical imaging interpretation, offering the potential to improve the efficiency and accuracy of radiology workflows. This study investigates the current state of AI-enhanced medical imaging interpretation and its impact on radiology workflow efficiency. We review the existing literature on AI applications in medical imaging interpretation, discuss the challenges and opportunities associated with integrating AI into radiology practice, and propose future research directions to further improve the use of AI in radiology.
References
Pillai, Aravind Sasidharan. "Multi-label chest X-ray classification via deep learning." arXiv preprint arXiv:2211.14929 (2022).
Tatineni, Sumanth. "Applying DevOps Practices for Quality and Reliability Improvement in Cloud-Based Systems." Technix international journal for engineering research (TIJER)10.11 (2023): 374-380.
Venigandla, Kamala. "Integrating RPA with AI and ML for Enhanced Diagnostic Accuracy in Healthcare." Power System Technology 46.4 (2022).
Nalluri, Mounika, et al. "MACHINE LEARNING AND IMMERSIVE TECHNOLOGIES FOR USER-CENTERED DIGITAL HEALTHCARE INNOVATION." Pakistan Heart Journal 57.1 (2024): 61-68.
Kolay, Srikanta, Kumar Sankar Ray, and Abhoy Chand Mondal. "K+ means: An enhancement over k-means clustering algorithm." arXiv preprint arXiv:1706.02949 (2017).
Khan, Murad, et al. "AI-POWERED HEALTHCARE REVOLUTION: AN EXTENSIVE EXAMINATION OF INNOVATIVE METHODS IN CANCER TREATMENT." BULLET: Jurnal Multidisiplin Ilmu 3.1 (2024): 87-98.
Shiwlani, Ashish, et al. "REVOLUTIONIZING HEALTHCARE: THE IMPACT OF ARTIFICIAL INTELLIGENCE ON PATIENT CARE, DIAGNOSIS, AND TREATMENT." JURIHUM: Jurnal Inovasi dan Humaniora 1.5 (2024): 779-790.
Sati, Madan Mohan, et al. "Two-Area Power System with Automatic Generation Control Utilizing PID Control, FOPID, Particle Swarm Optimization, and Genetic Algorithms." 2024 Fourth International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT). IEEE, 2024.
Pargaonkar, Shravan. "Unveiling the Challenges, A Comprehensive Review of Common Hurdles in Maintaining Software Quality." Journal of Science & Technology 2.1 (2021): 85-94.