Latest AI and machine learning research in clinical trials for healthcare professionals.
Timely access to current rheumatology guidelines at the point of care is challenging. We aimed to develop and evaluate the first Retrieval-Augmented Generation (RAG) system specifically designed for adult rheumatology, integrating European Alliance of Associations for Rheumatology (EULAR) and American College of Rheumatology (ACR) guidelines to provide rheumatologists with timely, evidence-based r...
Genomic testing has transformed treatment decisions for hormone receptor-positive, HER2-negative (HR+/HER2-) early breast cancer; however, it remains inaccessible to many patients worldwide due to high costs and logistical barriers. Here, we developed an artificial intelligence (AI) model using a multimodal deep learning approach that estimates Oncotype DX 21-gene recurrence scores (RS) from routi...
Coronary angiography (CAG) reports contain many details about coronary anatomy, lesion characteristics, and interventional procedures. However, their ...
Major depressive disorder (MDD) is a heterogeneous neuropsychiatric disorder with highly variable antidepressant outcomes. In randomized controlled tr...
Accurate interpretation of randomized controlled trial (RCT) results is essential for guiding clinical practice in oncology. Reporting “spin” can misr...
Fragile X Syndrome (FXS) is a rare neurodevelopmental disorder caused by a trinucleotide repeat expansion on the 5’ untranslated region of the FMR1 ge...
This pilot study is the first phase of a broader project aimed at developing an explainable artificial intelligence (AI) tool to support the ethical e...
Integrated digital diagnostics can support complex surgeries in many anatomic sites, and brain tumour surgery represents one of the most complex cases...
Artificial intelligence chatbots (AICs) are advanced systems capable of generating and processing human-like text, and are being increasingly integrat...
Prolonged fasting may benefit metabolic health, but data in healthy individuals remain limited. We performed a randomized, waitlist-controlled study (...
Target Trial Emulation (TTE) has emerged as a rigorous framework for causal inference using observational data, but its application in hypertension re...
State-of-the-art (SOTA) large language models (LLMs) are poised to revolutionize clinical medicine by transforming diagnostic, therapeutic, and interd...
The use of Artificial Intelligence (AI) methods in palliative care research is increasing. Most AI palliative care research involves the use of routin...
Mindfulness-based interventions (MBIs) have gained significant recognition as effective approaches for promoting mental health and well-being. With ra...
Early studies of large language models (LLMs) in clinical settings have largely treated artificial intelligence (AI) as a tool rather than an active c...
Artificial intelligence (AI) is increasingly used to support clinical decision-making, particularly in primary care triage. However, few studies have ...
This paper delivers a rigorous mixed-methods synthesis of conversational AI applications in mental health therapy, analyzing 47 randomized controlled ...
The early recognition of clinical deterioration in hospital inpatients continues to be a major challenge in healthcare. In this work, we proposed an i...
Precision-guided dual antiplatelet therapy (DAPT) duration post-percutaneous coronary intervention (PCI) remains a clinical challenge. Current risk st...
Artificial Intelligence-driven analysis of laparoscopic video holds potential to increase the safety and precision of minimally invasive surgery. Visi...