While artificial intelligence (AI) has demonstrated potential in automating clinical trial matching, most existing solutions rely on high-level structured data or oversimplified criteria. This study introduces a framework to structure and analyze eli...
Drug development is an expensive endeavor, with costs averaging $879.3 million and only 14.3% of them ultimately securing regulatory approval. One fundamental challenge is ensuring that the enrolled patient population in a clinical trial accurately r...
Using social media recruitment for public health research presents both opportunities and challenges. Despite its increased use, few studies have detailed the practical issues, challenges encountered, and alternative strategies available for social m...
BACKGROUND: Advancements in science and technology can exacerbate health disparities, particularly when there is a lack of diversity in clinical research, which limits the benefits of innovations for underrepresented communities. Programs like the Al...
Techniques in vascular and interventional radiology
Jul 14, 2025
Transjugular intrahepatic portosystemic shunt (TIPS) is a key therapeutic intervention in the management of portal hypertension and its complications, such as variceal bleeding, hepatic hydrothorax, and refractory ascites. TIPS has historically been ...
Therapeutic clinical trial enrollment does not match glioma incidence across demographics. Traditional statistical methods have identified independent predictors of trial enrollment; however, our understanding of the interactions between these factor...
PURPOSE OF REVIEW: Despite the pivotal role of randomized controlled trials (RCTs) in critical care research, many have failed to demonstrate significant benefits, particularly in nutrition interventions. This review highlights how patient heterogene...
BACKGROUND: The application of machine learning (ML) in predicting the requirement for total knee arthroplasty (TKA) at knee osteoarthritis (KOA) patients has been acknowledged. Nonetheless, the variables employed in the development of ML models are ...
PURPOSE OF REVIEW: The uses of generative artificial intelligence (GAI) technologies in medicine are expanding, with the use of large language models (LLMs) for matching patients to clinical trials of particular interest. This review provides an over...
BACKGROUND: Identifying patients eligible for clinical trials through eligibility screening is time and resource-intensive. Natural Language Processing (NLP) models may enhance clinical trial screening by extracting data from Electronic Health Record...
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