Latest AI and machine learning research in clinical trials for healthcare professionals.
With the widespread application of artificial intelligence in recruitment, algorithmic bias issues have become increasingly prominent, seriously threatening social fairness and job seekers' rights. Addressing the limitations of existing bias detection methods in detection granularity, fairness assessment, and interpretability, this study proposes a deep learning-based algorithmic bias detection fr...
BACKGROUND: Advanced and recurrent cervical cancer (CC) remains a clinical challenge due to limited therapeutic options and a poor 5-year survival rate (<20%). While immunotherapy has reshaped the treatment landscape, primary resistance driven by immune exclusion often limits its efficacy. This study aims to identify the key molecular determinants governing T-cell infiltration and to develop a rob...
BACKGROUND: Generative artificial intelligence (AI) is increasingly used in health communication and nursing education; however, its clinical reliabil...
BACKGROUND AND PURPOSE: Accurate MRI-based target delineation for hypopharyngeal squamous cell carcinoma (HPSCC) is clinically important but expertise...
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 ...
Global adoption of Level-3 (L3) autonomous driving systems (ADS) in commercial heavy goods vehicles (HGVs) remains limited, as concerns about reliabil...
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...
OBJECTIVE: Family caregivers of persons with dementia experience grief as the care recipients' dementia advances. Here, we explore how various interpe...
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...