Clinical Trials

Embracing the Digital Revolution: How Artificial Intelligence is Transforming Clinical Trials in Older Participants.

Artificial intelligence (AI) is revolutionizing clinical trials in geriatric populations by addressing the unique challenges of aging-related diseases and patient heterogeneity. Advanced AI techniques, including machine learning, deep learning, and AI-driven digital health platforms, enable intelligent patient stratification, risk prediction, and real-time monitoring tailored to older adults. AI f...

Advantages and challenges for utilization of generative artificial intelligence in clinical nursing practice: an integrative review.

BACKGROUND: Generative artificial intelligence (AI) has the potential to ease the administrative burden placed on nurses and to advance the quality and efficiency of care. Emerging nursing evidence suggests that increasing clinical complexity is associated with missed care, indicating that generative AI may play a role in supporting clinical judgment and streamlining nursing workflows. Despite the...

Digital literacy and scientific research ability among nursing postgraduates: The chain-mediating role of deep learning and research self-efficacy.

BACKGROUND: In the era of rapid digital transformation, it is crucial to cultivate research competence among nursing postgraduates to support innovati...

On flexible covariate adjustment under covariate-constrained randomization.

Covariate-constrained randomization is an effective treatment allocation procedure for controlling imbalance across multiple baseline covariates in ra...

Learning-aided observer design for improving autonomous vehicle safety.

This paper introduces a novel method for the enhancement of automated vehicle safety and efficiency during critical manoeuvres. The fundamental of the...

Evaluation of a Community-Based AI-Assisted Visual Impairment Screening Model for Performance, Operational Efficiency, Acceptability, Feasibility, and Costs: Protocol for a 2-Arm Pragmatic Randomized Controlled Trial.

BACKGROUND: Visual impairment (VI) affects more than 600 million people globally and significantly reduces quality of life. In Singapore, 20% of adult...

Minimally invasive surgery for advanced-stage ovarian cancer: a review of evidence and emerging paradigms.

Minimally invasive surgery has emerged as a promising approach to the management of advanced-stage epithelial ovarian cancer, particularly in the sett...

Prediction of Neoadjuvant Chemotherapy Efficacy for Locally Advanced Nasopharyngeal Carcinoma Using MRI-Based Deep Learning Features Combined with Vision Transformer.

RATIONALE AND OBJECTIVES: Predicting neoadjuvant chemotherapy (NACT) efficacy is vital for advanced nasopharyngeal carcinoma (LA-NPC) management. Exis...

Deep Learning-Derived Sarcopenia Marker Predicts Benefit from Anti-EGFR Therapy in Patients with RAS Wild-type Metastatic Colorectal Cancer.

PURPOSE: The benefit of treatment intensification in metastatic colorectal cancer (mCRC) may be influenced by host-related factors that are not accoun...

Predicting Non-Response to Multicomponent Treatment in Fibromyalgia: Development and Validation of a Machine Learning Model.

BACKGROUND: Multicomponent programs combining therapeutic exercise, cognitive-behavioral therapy, and pain neuroscience education demonstrate overall ...

Redefining Cytotechnologist Practice in Sweden: National Survey on Workload, Expanded Roles, and Future Competency Needs.

INTRODUCTION: Cytotechnologists have long been central to cervical cancer screening, although their education and job responsibilities differ markedly...

Movie features are hierarchically encoded in the dynamics of functional connectivity.

The perception of the external environment relies on a cascade of neural computations in the visual cortex, where stimulus features are represented hi...

Nano-antimicrobial peptides (Nano-AMPs) to combat resistant gram-negative bacteria.

The emergence of antimicrobial resistance (AMR) poses a critical threat to public health worldwide, making conventional antibiotics ineffective agains...

Multi-reader evaluation of deep learning-based auto-segmentation of eloquent brain arteriovenous malformation on MRA and white matter tractography in stereotactic radiosurgery.

OBJECTIVE: To minimize the radiation injury for white matter (WM) pathways during brain arteriovenous malformation (bAVM) stereotactic radiosurgery (S...

Telerehabilitation of chronic low back pain: protocol of a systematic review and network meta-analysis.

BACKGROUND: Chronic low back pain (CLBP) is among the most disabling musculoskeletal disorders worldwide. Traditional in-person rehabilitation is ofte...

Perception of Medical Speciality Professors towards Including Artificial Intelligence in their Curricula.

BACKGROUND: Medical residents have shown interest in artificial intelligence (AI) for their clinical and academic activities; however, research on the...

Agentic AI in Radiology: Evolution from Large Language Models to Future Clinical Integration.

The introduction of foundational models, specifically large language models, has promised a health care transformation. However, the field is rapidly ...

Updates in Central Retinal Artery Occlusion.

BACKGROUND: Central retinal artery occlusion (CRAO) is a vision-threatening neuro-ophthalmic emergency, analogous to acute ischemic stroke. Delayed pr...

Maternal and Pediatric Precision in Therapeutic Knowledge Portal (MPRINT-KP): Landscape Analysis of Pharmacology Research in Maternal and Pediatric Patient Populations.

Pregnant women and children have been underrepresented in clinical studies due to ethical concerns and perceived vulnerabilities. This resulted in a s...

The potential of artificial intelligence in clinical trials.

BACKGROUND: Clinical trials are an important part of evidence generation in medicine but remain burdened by escalating costs, inefficiencies and manua...