From conception to birth, artificial intelligence inherited the power of human reproduction, such as creativity, self-improvement and language use, etc. These abilities cannot be exercised in other places. The purpose of this paper is to explore the path of collaborative promotion based on artificial intelligence and digital economy. First, it outlines the scattered use of data by individuals at the two application levels of the digital economy and the systematic use of data by enterprises on large organizations. In this study, artificial intelligence and digital economy are introduced into the ability of project information sharing in the field of the enterprise project, and then their important role in improving the performance of enterprise project management is analyzed. Secondly, try to use interviews, scale analysis and logical subtraction to formulate the measurement standards of the digital environment and project information publishing ability, and provide basic data for follow-up research. The experimental results show that 54% of middle-level personnel said that the synergy between enterprise artificial intelligence and digital economy is very good, and they have a positive attitude toward exploring new ways to promote digital economy integration in the field of artificial intelligence.
Background: Artificial intelligence (AI) has the potential to enhance healthcare practices, including periodontology, by improving diagnostics, treatment planning and patient care. This study introduces 'PerioGPT', a specialized AI model designed to provide up-to-date periodontal knowledge using GPT-4o and a novel retrieval-augmented generation (RAG) system.
Aim: Anorectal diseases, often requiring surgical intervention and careful post-operative wound management, pose substantial challenges in healthcare. This study presents a novel application of artificial intelligence, specifically machine learning, aimed at improving the classification and analysis of post-surgical wound images. By doing so, it seeks to enhance patient outcomes through personalized and optimized wound care strategies.
White matter hyperintensities (WMH) of presumed vascular origin are a magnetic resonance imaging (MRI)-based biomarker of cerebral small vessel disease (CSVD). WMH are associated with cognitive decline and increased risk of stroke and dementia, and are commonly observed in aging, vascular cognitive impairment, and neurodegenerative diseases. The reliable and rapid measurement of WMH in large-scale multisite clinical studies with heterogeneous patient populations remains challenging, where the diversity of imaging characteristics across studies adds additional complexity to this task.
Background: Percutaneous extracorporeal membrane oxygenation (ECMO) is administered to pediatric patients with cardiogenic shock or cardiac arrest. The traditional method uses focal echocardiography to complete the left ventricular measurement. However, echocardiographic determination of the ejection fraction (EF) by manual tracing of the endocardial borders is time consuming and operator dependent.
