Latest AI and machine learning research in clinical trials for healthcare professionals.
Prompt engineering techniques which aid in the use of generative artificial intelligence to address classification tasks have expanded considerably in the last 2 years. The success of such methods varies depending on context, and their efficacy in extracting structured data from unstructured medical text is not well understood. In this paper, five large language prompting strategies were evaluated...
Objectives. This research aims to provide information on factors that may affect the accident susceptibility of workers by using various individual characteristics of workers as variables with machine learning algorithms, and the effects of occupational health and safety (OHS) training and workers' safety awareness within this interaction. Methods. Research data were obtained through surveys admin...
AIMS: Accurate stratification of mortality risk is essential for management of chronic coronary syndromes (CCS), but existing models focus primarily o...
BACKGROUND: Asthma-related deaths in the United Kingdom are the highest in Europe, and only 30% of patients access basic care. There is a need for alt...
OBJECTIVE: Maxillary canine impaction affects approximately 1-3% of the population and presents diagnostic, prognostic, and therapeutic challenges. Th...
The advancements in computer vision have opened doors to estimate crash risks in real-time and revisit traffic signal systems to optimize safety and e...
BACKGROUND: Triage errors in emergency departments (EDs), including undertriage and overtriage, pose significant risks to patient safety and resource ...
OBJECTIVE: Golf carts are increasingly sharing public roads with other vehicles, creating new safety challenges due to their design limitations and ga...
UNLABELLED: We assessed feasibility and effectiveness of AI-based VF screening in CT, integrated with a local FLS. The system identified VFs in 14% of...
BACKGROUND: Ferroptosis plays a critical role in immune regulation and tumor microenvironment remodeling. However, its therapeutic potential in enhanc...
BACKGROUND: Diabetes is a chronic condition requiring long-term management, and continuous health education is vital for improving disease awareness a...
This article provides a systematic review of the advances in the precise diagnosis and management of immune-related adverse events (irAEs) induced by ...
Artificial intelligence (AI) is increasingly used in mental health, yet its rehabilitation-oriented applications in schizophrenia have not been system...
INTRODUCTION: Cancer research has become increasingly data-intensive, with digital pathology, imaging, and genomic sequencing generating vast, heterog...
Deep brain stimulation (DBS) for treatment-resistant depression (TRD) is challenged by significant individual variability in efficacy and unclear neur...
BACKGROUND & AIMS: Evidence about the effect of artificial intelligence (AI) on upper endoscopy in multicenter, randomized controlled trials is lackin...
BACKGROUND: Epilepsy is a chronic neurological disorder characterized by altered cortical excitability. The disorder is often associated with psycholo...
BACKGROUND: There is an urgent need to evaluate the efficacy of novel therapeutics that have been approved for use in adults with IgA nephropathy (IgA...
INTRODUCTION: Total tumor number (TTN) and total tumor volume (TTV) reflect tumor burden and have been linked to outcomes in metastatic colorectal can...
Monoclonal antibody (mAb)-based therapies have revolutionized modern medicine, offering highly specific and effective treatments for a wide range of d...