Fernandes, José Fernandes e

Motivation: The price of medical treatment continues to rise due to (i) an increasing population; (ii) an aging human growth; (iii) disease prevalence; (iv) a rise in the frequency of patients that utilize health care services; and (v) increase in the price. Objective: Artificial Intelligence (AI) is already well-known for its superiority in various healthcare applications, including the segmentation of lesions in images, speech recognition, smartphone personal assistants, navigation, ride-sharing apps, and many more. Our study is based on two hypotheses: (i) AI offers more economic solutions compared to conventional methods; (ii) AI treatment offers stronger economics compared to AI diagnosis. This novel study aims to evaluate AI technology in the context of healthcare costs, namely in the areas of diagnosis and treatment, and then compare it to the traditional or non-AI-based approaches. Methodology: PRISMA was used to select the best 200 studies for AI in healthcare with a primary focus on cost reduction, especially towards diagnosis and treatment. We defined the diagnosis and treatment architectures, investigated their characteristics, and categorized the roles that AI plays in the diagnostic and therapeutic paradigms. We experimented with various combinations of different assumptions by integrating AI and then comparing it against conventional costs. Lastly, we dwell on three powerful future concepts of AI, namely, pruning, bias, explainability, and regulatory approvals of AI systems. Conclusions: The model shows tremendous cost savings using AI tools in diagnosis and treatment. The economics of AI can be improved by incorporating pruning, reduction in AI bias, explainability, and regulatory approvals.

Despite the publication of several national/international guidelines, the optimal management of patients with asymptomatic carotid stenosis (AsxCS) remains controversial. This article compares 3 recently released guidelines (the 2020 German–Austrian, the 2021 European Stroke Organization [ESO], and the 2021 Society for Vascular Surgery [SVS] guidelines) vs the 2017 European Society for Vascular Surgery (ESVS) guidelines regarding the optimal management of AsxCS patients. The 2017 ESVS guidelines defined specific imaging/clinical parameters that may identify patient subgroups at high future stroke risk and recommended that carotid endarterectomy (CEA) should or carotid artery stenting (CAS) may be considered for these individuals. The 2020 German–Austrian guidelines provided similar recommendations with the 2017 ESVS Guidelines. The 2021 ESO Guidelines also recommended CEA for AsxCS patients at high risk for stroke on best medical treatment (BMT), but recommended against routine use of CAS in these patients. Finally, the SVS guidelines provided a strong recommendation for CEA+BMT vs BMT alone for low-surgical risk patients with >70% AsxCS. Thus, the ESVS, German–Austrian, and ESO guidelines concurred that all AsxCS patients should receive risk factor modification and BMT, but CEA should or CAS may also be considered for certain AsxCS patient subgroups at high risk for future ipsilateral ischemic stroke.