Latest AI and machine learning research in information technology for healthcare professionals.
Reliable prediction of pediatric obesity can offer a valuable resource to providers, helping them engage in timely preventive interventions before the disease is established. Many efforts have been made to develop ML-based predictive models of obesity, and some studies have reported high predictive performances. However, no commonly used clinical decision support tool based on existing ML models...
The rise of digital platforms has led to an increasing reliance on technology-driven, home-based healthcare solutions, enabling individuals to monitor their health and share information with healthcare professionals as needed. However, creating an efficient care plan management system requires more than just analyzing hospital summaries and Electronic Health Records (EHRs). Factors such as indiv...
Over 30 million Americans are affected by Type II diabetes (T2D), a treatable condition with significant health risks. This study aims to develop an...
Human health is increasingly threatened by exposure to hazardous substances, particularly persistent and toxic chemicals. The link between these sub...
Disparities in access to healthcare have been well-documented in the United States, but their effects on electronic health record (EHR) data reliabi...
Foundation Models (FMs) trained on Electronic Health Records (EHRs) have achieved state-of-the-art results on numerous clinical prediction tasks. Ho...
This paper explores the relatively underexplored application of Positive Unlabeled (PU) Learning and Negative Unlabeled (NU) Learning in the cyberse...
The Internet of Things (IoT) has transformed healthcare, facilitating remote patient monitoring, enhanced medication adherence, and chronic disease ...
Artificial intelligence (AI) and digital public infrastructure (DPI) are two technological developments that have taken center stage in global polic...
As command-line interfaces remain integral to high-performance computing environments, the risk of exploitation through stealthy and complex command...
In the healthcare sector, the application of deep learning technologies has revolutionized data analysis and disease forecasting. This is particular...
With the rapid advancement of artificial intelligence and deep learning, medical image analysis has become a critical tool in modern healthcare, sig...
The goal of this work was to compute the semantic similarity among publicly available health survey questions in order to facilitate the standardiza...
Accurate prediction of medical conditions with straight past clinical evidence is a long-sought topic in the medical management and health insurance...
Large Language Models (LLMs) have demonstrated remarkable proficiency in natural language processing; however, their application in sensitive domain...
This research explores the integration of blockchain technology in healthcare, focusing on enhancing the security and efficiency of Electronic Healt...
Electronic healthcare records (EHR) contain a huge wealth of data that can support the prediction of clinical outcomes. EHR data is often stored and...
Anti-Muslim hate speech has emerged within memes, characterized by context-dependent and rhetorical messages using text and images that seemingly mi...
OBJECTIVE: This systematic review aimed to provide a comprehensive overview of the application of machine learning (ML) in predicting multiple adverse...
Advancements in machine learning (ML) are making artificial intelligence more feasible in dermatology, with promising results for diagnosing skin canc...