Latest AI and machine learning research in patient safety / risk management for healthcare professionals.
Disparities in disability services between two-year and four-year higher education institutions pose challenges to achieving equitable access to accommodations. This study applies a robust quantitative analysis of the National Center for Education Statistics (NCES) dataset, utilizing multiple regression models and exploratory factor analysis to identify institutional characteristics that impact di...
In this paper, we explore the paradox of trust and vulnerability in human-machine interactions, inspired by Alexander Reben's BlabDroid project. This project used small, unassuming robots that actively engaged with people, successfully eliciting personal thoughts or secrets from individuals, often more effectively than human counterparts. This phenomenon raises intriguing questions about how tru...
Federated learning (FL) is a distributed training paradigm that enables collaborative learning across clients without sharing local data, thereby pr...
The U.S. Decennial Census serves as the foundation for many high-profile policy decision-making processes, including federal funding allocation and ...
Privacy is dynamic, sensitive, and contextual, much like our emotions. Previous studies have explored the interplay between privacy and context, pri...
A firm seeks to analyze a dataset and to release the results. The dataset contains information about individual people, and the firm is subject to s...
Soft-tissue and bone tumours (STBT) are rare, diagnostically challenging lesions with variable clinical behaviours and treatment approaches. This sy...
Electronic health data concerning implantable medical devices (IMD) opens opportunities for dynamic real-world monitoring to assess associated risks r...
Privacy research has attracted wide attention as individuals worry that their private data can be easily leaked during interactions with smart devic...
Biological research spans scales and methodologies, generating complex data visualizations such as images, text, numbers, networks, and maps. With i...
This case study describes how one educator approached the incorporation of generative AI into a graduate-level introductory nursing informatics course...
2023 was the year the world woke up to generative AI, and 2024 is the year policymakers are responding more firmly. Importantly, this policy momentu...
As the U.S. Census Bureau implements its controversial new disclosure avoidance system, researchers and policymakers debate the necessity of new pri...
To address the rapid evolution of artificial intelligence in medical imaging, the authors present the Checklist for Artificial Intelligence in Medical...
Large language models (LLMs) use autoregression to generate text in response to queries. Crafting an appropriate prompt to elicit the desired response...
Tuberculosis, which primarily affects developing countries, remains a significant global health concern. Since the 2010s, the role of chest radiograph...
To systematically evaluate artificial intelligence applications for diagnostic and treatment planning possibilities in pediatric dentistry. PubMed, ...
BACKGROUND: Medical imaging techniques have improved to the point where security has become a basic requirement for all applications to ensure data se...
Literacy in research studies of artificial intelligence (AI) has become an important skill for radiologists. It is required to make a proper assessmen...