Latest AI and machine learning research in clinical trials for healthcare professionals.
Traditional testing methods in pharmaceutical development can be time-consuming and costly, but in silico evaluation tools can offer a solution. Our in-house Active-IT system, a Ligand-Based Virtual Screening (LBVS) tool, was developed to predict the biological and pharmacological activities of small organic molecules. It includes four independent modules for generating molecular descriptors (3D-P...
Gliomas are the most prevalent form of primary brain tumours. Recently, targeting the PD-1 pathway with immunotherapies has shown promise as a novel glioma treatment. However, not all patients experience long-lasting benefits, underscoring the necessity to discover reliable biomarkers for predicting treatment outcomes. This study applied a range of advanced artificial intelligence methods to ident...
Cardiovascular disease refers to any critical condition that impacts the heart. Because heart diseases can be life-threatening. Researchers are focu...
Text-to-image models are increasingly popular and impactful, yet concerns regarding their safety and fairness remain. This study investigates the ab...
Combination therapies have emerged as a promising approach for treating complex diseases, particularly cancer. However, predicting the efficacy and sa...
Randomized clinical trials are the gold standard for establishing the efficacy and safety of cardiovascular therapies. However, current pivotal trials...
Navigating the regulatory frameworks that ensure the safety and efficacy of medical devices can be challenging, especially across different regions....
OBJECTIVE: The objective of our research is to conduct a comprehensive review that aims to systematically map, describe, and summarize the current uti...
\textbf{Trial design} Crossover randomized controlled trial. \textbf{Methods} An AI tool, Easy-ICD, was developed to assist clinical coders and was ...
Artificial Intelligence (AI) has rapidly evolved over the past decade and has advanced in areas such as language comprehension, image and video reco...
In this work we revisit the arithmetic and bit complexity of Hermitian eigenproblems. Recently, [BGVKS, FOCS 2020] proved that a (non-Hermitian) mat...
Operationalizing AI ethics and safety principles and frameworks is essential to realizing the potential benefits and mitigating potential harms caus...
In today's world, the significance of explainable AI (XAI) is growing in robotics and point cloud applications, as the lack of transparency in decis...
The decomposition of high-density surface electromyography (HD-sEMG) signals into motor unit discharge patterns has become a powerful tool for inves...
When assisting people in daily tasks, robots need to accurately interpret visual cues and respond effectively in diverse safety-critical situations,...
Randomized controlled trials (RCTs) can be used to generate guarantees on treatment effects. However, RCTs often spend unnecessary resources explori...
Decoding nervous system activity is a key challenge in neuroscience and neural interfacing. In this study, we propose a novel neural decoding system...
We present the first study of the Public Register of Licensed Persons and Registered Institutions maintained by the Hong Kong Securities and Futures...
The rapid development of online recruitment platforms has created unprecedented opportunities for job seekers while concurrently posing the signific...
Text-based image generation models, such as Stable Diffusion and DALL-E 3, hold significant potential in content creation and publishing workflows, ...