Emerging Technologies Paper

Emerging Technologies Name Institution Course Code and Title Instructor Date Summary of the article: HIMSS, 2024 Global Health Conference The 2024 HIMSS Global Health Conference and Exhibition attracted over 30,000 people representing more than 70 countries to Orlando (HIMSS, 2024). According to HIMSS (2024), these people focused on the convergence of technology, people, and processes in healthcare. The prominent topics included artificial intelligence, cybersecurity, robotics, and digital health. The focus was on artificial intelligence and how it would be able to drive health equity and improve the different aspects of healthcare, including climate change and sustainability. The conference featured almost 500 speakers and more than 1,000 exhibitors. There were several notable developments including new partnerships over recent years, the launch of the Hosted Buyer Program, and additional new opportunities for start-ups (HIMSS, 2024). It also completed one very important partnership with Informa Markets, elevating the whole experience for attendees. The emerging technology described in this article is Artificial Intelligence (AI) in health. According to Esmaeilzadeh (2020), AI uses higher algorithms and data analysis to help in making decisions that can improve and better patient outcomes and resolve global health challenges. Example of Technology My future clinical practice area involves working as a nurse practitioner with a specialization in managing chronic diseases. AI in this area could help improve care delivery by analyzing big data to predict the progression of the disease, personalize treatment plans, and possibly identify complications before they occur (Jiang et al., 2017). For example, AI-based risk models might mine the data from EHRs for patients most at risk of diabetes-related complications. This will aid in presenting interventions earlier and in a more focused manner. Legal, Ethical, and Safety Considerations Data privacy as a legal issue is at the center of the legal debate in the application of AI in healthcare. This is because a lot of patient data is required to run AI systems. This raises questions as to how this data is obtained, stored, and utilized (Naik et al., 2022). In addition,...