Clinical data warehouses maximize veracity via schema-on-write and ACID guarantees, but ETL rework, limited modality support, ...

The use of Artificial Intelligence (AI) and Machine Learning (ML) in clinical research is rapidly evolving, offering a glimpse into a future where medical innovation is driven by data-driven ...

MI-Common Data Model: Extending Observational Medical Outcomes Partnership-Common Data Model (OMOP-CDM) for Registering Medical Imaging Metadata and Subsequent Curation Processes The Osteosarcoma ...

Clinical genomics laboratories are no longer limited to research settings; they are increasingly integrated into routine ...

Palliative Radiotherapy Near the End of Life: An Analysis of Factors Influencing the Administration of Radiotherapy in Advanced Tumor Disease Clinical trial activity in radiation oncology has ...

Despite rapid growth, only 9.2% of DCTs are multiregional and over 80% single-country, indicating challenges in international implementation. 2 With regulatory agencies 4–7 underscoring risk-based ...

In the early 2000s, Paul Harris, a research informatics faculty member and bioengineer at Vanderbilt University Medical Center, noticed a pressing problem. While working with research teams, he found ...

As the FDA formally recognizes real-world evidence as eligible confirmatory evidence for drug approval, sponsors face a growing imperative to build the data infrastructure, organizational alignment, ...

Increasing clinical trial participant representation in clinical research is critical to developing new medicines that are safe and effective for patients in need. However, historical clinical ...