Latest AI and machine learning research in clinical trials for healthcare professionals.
OBJECTIVES: Selective posterior thoracic fusion (sPTF) for Lenke 1/2 adolescent idiopathic scoliosis (AIS) aims to reconcile multi-planar correction with motion preservation. Nevertheless, postoperative coronal imbalance (CIB) frequently compromises these objectives. This study developed an interpretable machine learning architecture to stratify CIB risk and identify key predictors. METHODS: Data ...
BACKGROUND: Differences in social media addiction, anxiety, and parenting self-efficacy according to maternal employment status have important implications for maternal and child public health. However, evidence comparing these psychosocial outcomes between employed and non-employed mothers of infants remains limited, hindering the development of targeted maternal and child health interventions. T...
Artificial intelligence (AI) is increasingly being used to support clinical research, but its value in vaccine clinical trials requires careful eviden...
PURPOSE: Previous literature has identified multiple risk factors for anxiety among individuals with cancer. However, the relative importance across m...
This review highlights the problem of protein molecule aggregation, which represents a significant challenge in the field of biopharmaceuticals. Prote...
Accurate and timely mortality prediction is essential for nursing clinical decision-making in intensive care units (ICUs). Although the Sequential Org...
Successful deployment of medical artificial intelligence (AI) systems should start with formulating clear goals and understanding organisational workf...
BACKGROUND: Hypertension remains the leading modifiable risk factor for cardiovascular morbidity and mortality worldwide, with persistently inadequate...
BACKGROUND: Current guidelines recommend pancolonic chromoendoscopy (pCE) over white light endoscopy (WLE) alone for colorectal neoplasia (CRN) detect...
BACKGROUND: The rapid integration of artificial intelligence (AI) into healthcare has amplified the need for nurses who can engage with AI-supported s...
BACKGROUND: Colorectal cancer (CRC) screening relies on structured risk assessment and guideline-concordant communication, which remain challenging to...
OBJECTIVE: To evaluate the diagnostic accuracy and clinical reasoning of three frontier large language models (LLMs) across standardized pediatric gas...
BACKGROUND: Pharmacovigilance aims to protect patient safety by identifying and managing adverse events associated with pharmaceuticals. Determining t...
BACKGROUND: Artificial intelligence (AI)-based computer-aided detection (CADe) systems improve adenoma detection in average-risk colorectal cancer scr...
U.S. colleges and schools of pharmacy face mounting challenges in sustaining robust research programs, supporting early-stage investigators, modernizi...
The current trend of deploying machine learning models as remote services obscures which specific models users are interacting with, exacerbating an a...
We consider the reality of deploying artificial intelligence (AI) in safety-critical systems, such as autonomous vehicles, medical diagnoses and weath...
In this opinion piece, we present the view that the safety and security of end users should be placed at the heart of the design and development of an...
Burnout remains one of the defining occupational hazards of healthcare in the United States, and it spares no one on the care team: physicians, nurses...
BACKGROUND: Large language models (LLMs) are increasingly embedded in conversational agents for cardiometabolic care. These systems could support self...