BACKGROUND: Large language models (LLMs) are becoming increasingly popular in clinical trial design but have been underused in research proposal development.
Oncology clinical trials play a pivotal role in the development of new therapeutic options; however, their implementation remains an extremely costly and time-consuming process. Artificial intelligence can open new horizons in the design and conduct ...
While artificial intelligence (AI) has demonstrated potential in automating clinical trial matching, most existing solutions rely on high-level structured data or oversimplified criteria. This study introduces a framework to structure and analyze eli...
Artificial intelligence holds the potential to enhance the efficiency of clinical research. Yet, like all innovations, its impact is dependent upon target user uptake and adoption. As efforts to leverage artificial intelligence for clinical trial scr...
Drug development is an expensive endeavor, with costs averaging $879.3 million and only 14.3% of them ultimately securing regulatory approval. One fundamental challenge is ensuring that the enrolled patient population in a clinical trial accurately r...
BACKGROUND: As clinical trials scale up and grow more complex, researchers are facing mounting challenges, including inefficient participant recruitment, complex data management, and limited risk monitoring. These issues not only increase the workloa...
BACKGROUND: Pediatric drug clinical trials are essential for ensuring the accessibility and safety of medications intended for children. In recent years, the Chinese government has implemented various measures to foster the development of pediatric d...
Ischemic stroke remains a leading cause of disability and mortality worldwide. Currently, there are no effective therapeutic strategies to promote post-stroke nerve repair and regeneration in clinical practice. Stem cells, characterized by self-renew...
The integration of mobile health (mHealth) technologies into decentralized clinical trials (DCTs) may represent a paradigm shift in oncology research, offering innovative solutions to longstanding challenges in clinical trial design and execution. mH...
BACKGROUND: We aimed to develop an actionable and feasible prospective clinical model to estimate toxicity risk to assist chimeric antigen receptor (CAR) T-cell therapy providers with the management of patients with relapsed and/or refractory large B...
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