As genomic research becomes more complex and data-rich, artificial intelligence (AI) has
emerged as a crucial tool for processing and analyzing high-dimensional genomic data …

Background In recent years, health data collected during the clinical care process have
been often repurposed for secondary use through clinical data warehouses (CDWs), which …

PURPOSE Accurate and efficient data collection is a challenge for quality improvement
initiatives and clinical research. We describe the development of a custom electronic health …

Objective: This review aims to analyze the application of natural language processing (NLP)
techniques in cancer research using electronic health records (EHRs) and clinical notes …

Introduction Real-world evidence is important in regulatory and funding decisions. Manual
data extraction from electronic health records (EHRs) is time-consuming and challenging to …

Motivation Despite the increasing evidence of utility of genomic medicine in clinical practice,
systematically integrating genomic medicine information and knowledge into clinical …

Oncology like most medical specialties, is undergoing a data revolution at the center of
which lie vast and growing amounts of clinical data in unstructured, semi-structured and …

The sequencing of the first human genome led to expectations of the widespread use of
genetics in medicine. However, assessing the true impact of genetic testing on clinical …