相关论文: Assessing the Acceptance of Clinical Decision Supp…
Machine learning is used in medicine to support physicians in examination, diagnosis, and predicting outcomes. One of the most dynamic area is the usage of patient generated health data from intensive care units. The goal of this paper is…
Electric vehicles (EVs) represent a significant advancement in automotive technology, utilizing electricity as a power source instead of traditional fossil fuels, while incorporating sophisticated navigation and autopilot systems. These…
Radiology report generation (RRG) is commonly formulated as a single-path generation task, where a multimodal large language model (MLLM) produces one decoded report as the final output. While recent progress has largely been driven by…
Cloud computing is proved to be an effective computing technology for organisations through the advantages that it offers such as cost-effectiveness, IT technical agility and scalability, enhancing businesses processes, and increasing…
Recognizing, assessing, countering, and mitigating the biases of different nature from heterogeneous sources is a critical problem in designing a cognitive Decision Support System (DSS). An example of such a system is a cognitive…
The specification and validation of robotics applications require bridging the gap between formulating requirements and systematic testing. This often involves manual and error-prone tasks that become more complex as requirements, design,…
Cloud computing is a technology that has become increasingly popular over the past decade within several enterprises. This popularity can be attributed to its benefits, including lower operating costs, improved computational capabilities,…
We study the use of exchangeable multi-task Gaussian processes (GPs) for causal inference in panel data, applying the framework to two settings: one with a single treated unit subject to a once-and-for-all treatment and another with…
Digital government innovation is being recognised as a solution to many problems faced by governments in providing services to their citizens. It is especially important for low-income countries where there are resource constraints. This…
The aim of this study is to examine the effect of Information and Communication Technology (ICT) development on country's scientific ranking as measured by H-index. Moreover, this study applies ICT development sub-indices including ICT Use,…
In the past decade a surge in the amount of electronic health record (EHR) data in the United States, attributed to a favorable policy environment created by the Health Information Technology for Economic and Clinical Health (HITECH) Act of…
Recent advancements in technology have necessitated a paradigm shift in the people use technology necessitating a new research field called Human-Machine collaboration. ChatGPT, an Artificial intelligence (AI) assistive technology, has…
In recent years, there has been a growing recognition of the need to incorporate lay-people's input into the governance and acceptability assessment of AI usage. However, how and why people judge acceptability of different AI use cases…
The early development and deployment of hospital and healthcare information systems have encouraged the ongoing digitization of processes in hospitals. Many of these processes, which previously required paperwork and telephone arrangements,…
AI applications are increasingly being introduced into digital health. While technical performance has advanced rapidly, successful deployment mainly depends on consumer attitudes, especially to patient-facing applications. However, most…
Artificial intelligence (AI) is rapidly transforming public-sector processes worldwide, yet standardized measures rarely address the unique drivers, governance models, and cultural nuances of the Gulf Cooperation Council (GCC) countries.…
In this paper, the adoption patterns of Generative Artificial Intelligence (AI) tools within software engineering are investigated. Influencing factors at the individual, technological, and societal levels are analyzed using a mixed-methods…
A growing gap between progress in biological knowledge and improved health outcomes inspired the new discipline of translational medicine, in which the application of new knowledge is an explicit part of a research plan. Abramson and…
Despite the growing clinical adoption of large language models (LLMs), current approaches heavily rely on single model architectures. To overcome risks of obsolescence and rigid dependence on single model systems, we present a novel…
Importance: We introduce a novel Retrieval Augmented Generation (RAG)-Large Language Model (LLM) framework as a Clinical Decision Support Systems (CDSS) to support safe medication prescription. Objective: To evaluate the efficacy of…