Latest AI and machine learning research in clinical trials for healthcare professionals.
BACKGROUND: Generative artificial intelligence (AI) is increasingly used in health communication and nursing education; however, its clinical reliability remains uncertain. Breastfeeding education requires accurate, readable, and clinically applicable materials. AIM: The purpose of this explanatory sequential mixed-methods study was to evaluate AI-generated breastfeeding education brochures in ter...
BACKGROUND AND PURPOSE: Accurate MRI-based target delineation for hypopharyngeal squamous cell carcinoma (HPSCC) is clinically important but expertise dependent. We aimed to develop a multicenter-validated tri-sequence deep-learning model, determine whether AI assistance narrows contouring expertise gap, and explore quality-aware low-overlap risk modeling to inform deployment support. MATERIALS AN...
BACKGROUND: Early and reliable grading of diabetic retinopathy is important for preventing avoidable vision loss. Although deep learning methods have ...
BACKGROUND AND OBJECTIVES: General purpose vision-language models (VLMs) demonstrate impressive capabilities, but their opaque training on uncurated i...
BACKGROUND: Cardiac rehabilitation (CR) improves functional capacity and outcomes in patients with heart failure (HF). However, a clinically significa...
BACKGROUND: Artificial intelligence (AI)-based conversational tools are rapidly expanding within mental health care as a means of increasing access an...
AIMS: Achieving optimal glycaemic control remains a burden for many people with diabetes on intensive insulin treatment. The MELISSA trial aims to cli...
Personalized data-driven interventions for depression are much needed. Here, we leveraged N-of-1 machine learning (ML) to optimally target behavioral ...
BACKGROUND: Colorectal cancer (CRC) leads to heavy disease and economic burdens globally. Early screening such as colonoscopy has been demonstrated to...
OBJECTIVE: To explore the clinical value of AI-assisted pulmonary rehabilitation education in patients undergoing thoracoscopic surgery for lung cance...
BACKGROUND: As digital health solutions gain traction, there is an urgent need for effective, person-centered stress management tools for employees. A...
With the widespread application of the engineering-procurement-construction (EPC) delivery model in large-scale infrastructure and complex industrial ...
BACKGROUND: Focused ultrasound (FUS) has achieved favorable results in the treatment of allergic rhinitis (AR). However, some patients still have poor...
The global threat of antibiotic resistance necessitates intelligent design strategies for next-generation antibacterial nanomaterials. Herein, high-ef...
PURPOSE: This study aims to evaluate the efficacy of large language models (LLMs) in health management for urological and andrological conditions by c...
Expensive dairy products like ghee are at high risk of hazardous adulteration with cheaper fats, and traditional testing approaches such as FTIR devic...
OBJECTIVE: To compare an artificial intelligence-based design workflow with a manual CAD workflow in terms of design time, vertical marginal misfit, d...
BACKGROUND: The overuse of antibiotics in both veterinary and human medicine has resulted in the emergence of antibiotic-resistant bacteria, prompting...
OBJECTIVES: The use of prostate magnetic resonance imaging (MRI) is increasing, and coverage often captures substantial portions of the pelvis, visual...
OBJECTIVE: The purpose of this study was to develop and evaluate a method for synthesizing 3D urothelial phase images in CTU examinations from the dua...