Latest AI and machine learning research in clinical trials for healthcare professionals.
Artificial intelligence (AI) is rapidly evolving worldwide, enabling greater flexibility and applicability to the field of language translation within healthcare. Australia is currently one of the most culturally and linguistically diverse countries in the world, creating a growing pressure on translators to ensure there is equitable and culturally safe access to healthcare services. Emerging rese...
The widespread adoption of computed tomography has increased the detection of lung nodules. However, deep learning methods for classification of benign and malignant nodules often fail to comprehensively integrate global and local features, and most of these methods have not been validated through clinical trials. Here we developed DeepFAN, a transformer-based model trained on more than 10,000 pat...
PURPOSE OF REVIEW: This review examines recent advances in pediatric airway management, including emerging technologies, updated guidelines, and innov...
BACKGROUND AND OBJECTIVE: The automated recognition of surgical phases in intraoperative videos represents a critical milestone in the digital transfo...
BACKGROUND: Technological advancements and widespread internet connectivity have fundamentally transformed data collection across academic disciplines...
BACKGROUND: Digital twins (DTs) offer a paradigm for health care by enabling data-driven, simulation-capable representations of individual health traj...
BACKGROUND: Oral medications are commonly used in the treatment of breast cancer (BC), despite high rates of nonadherence. As adherence is fundamental...
OBJECTIVE: Although a range of evidence-based treatments for eating disorders exist, treatment response varies substantially. The ability to match ind...
BACKGROUND: Therapeutic ultrasound has emerged as a promising noninvasive or minimally invasive modality in ophthalmology, offering novel solutions ac...
BACKGROUND AND OBJECTIVES: Podcasts can make health evidence easier to follow, but it is unclear whether artificial intelligence (AI)-assisted product...
BACKGROUND: All patients with rifampicin-resistant tuberculosis should receive a short course of effective treatment. We aimed to evaluate the effecti...
Equity, diversity, and inclusion (EDI) are fundamental to achieving fairness and representation in radiological research and practice. This review aim...
BACKGROUND: Treatment-as-usual (TAU) conditions are intended to reflect the support typically received in routine treatment settings. For digital ment...
BACKGROUND: Artificial intelligence (AI) is increasingly recognized for its potential to transform cancer care. However, much of the existing evidence...
In blasting engineering, accurate prediction of peak particle velocity (PPV) is essential to ensuring the safety of surrounding structures. In machine...
BACKGROUND: Radiologist burnout affects approximately 40% of US radiologists. Large language models (LLMs) may improve workflow efficiency, but real-w...
Combination therapy is an essential strategy for treating complex diseases. However, unintended drug-drug interactions (DDIs) can compromise therapeut...
This research presents a robust real-time driver drowsiness detection system employing deep learning, attention mechanisms, and explainable AI (XAI) t...
In recent years, the integration of spectroscopic techniques with machine learning algorithms has emerged as a powerful analytical paradigm, demonstra...