Latest AI and machine learning research in clinical trials for healthcare professionals.
An LLM-based AI tool significantly improved identification of potentially eligible patients and screening efficiency for IBD clinical trials, outperforming physician referrals by screening electronic medical records and generating ranked candidate lists based on trial inclusion/exclusion criteria, thereby enhancing trial recruitment.
IMPORTANCE: Depression most commonly first emerges during adolescence, making early prevention critical. While school-based mindfulness training (SBMT) offers a scalable prevention approach with broad reach, evidence of its effectiveness is mixed, and there is a compelling case for a more personalized approach to prevention. OBJECTIVE: To develop a data-driven algorithm from baseline characteristi...
BACKGROUND: Sensor-based footwear is increasingly discussed as a promising tool for mobility monitoring and fall-risk assessment, yet its applicabilit...
This study evaluated the accuracy, consistency, and clinical appropriateness of responses generated by large language models (LLMs) to frequently aske...
The deployment of artificial intelligence (AI) translation tools in healthcare is accelerating rapidly, yet regulatory frameworks lag dangerously behi...
INTRODUCTION: Soft robotic gloves (SRGs) integrated with brain-computer interfaces (BCIs) have demonstrated potential in facilitating motor recovery a...
Counterfeit and substandard pharmaceuticals represent a critical global health crisis, with the World Health Organisation (WHO) reporting that falsifi...
BACKGROUND: Catheter-based urodynamic studies remain the standard for diagnosing lower urinary tract dysfunction, but are limited by discomfort, infec...
OBJECTIVE: To investigate how AI-powered chatbots influence patient perceptions of pharmacist roles compared to traditional educational methods and ev...
Artificial intelligence (AI) is increasingly embedded in language education, and learners' acceptance of AI, together with their multilingual learning...
The presence of mono- and dual-species biofilms in food industry poses a critical threat with respect to food security and safety at a global scale. T...
AIMS: Heart failure (HF) requires scalable strategies to detect decompensation early and reduce hospitalizations. Existing telemonitoring tools are of...
BACKGROUND: Automated approaches to cognitive impairment screening may soon achieve sufficient levels of accuracy for clinical implementation but they...
Safety instrumented systems (SISs) play a crucial role in preventing major accidents in the petrochemical industry. This study investigates the impact...
INTRODUCTION: Integrated digital diagnostics can support complex surgeries in many anatomic sites, and brain tumour surgery represents one of the most...
Artificial intelligence (AI) and machine learning (ML) are beginning to enhance key workflows across blood banking (BB) and transfusion medicine (TM),...
Recently developed machine learning-enabled approaches to quality tolerance limit (QTL) surveillance offer efficiencies over labour-intensive source d...
UNLABELLED: Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is characterized by heightened inflammation and immune dysregulation,...
OBJECTIVE: To develop models within pediatric telemedicine that identify potentially "sick" cases for additional safety checks and integrate those mod...
Computer self-efficacy plays a crucial role in users' AI usage, but the research on this aspect is inadequate in quantitative terms. This study, groun...