PURPOSE The advancement of natural language processing (NLP) has promoted the use
of detailed textual data in electronic health records (EHRs) to support cancer research and …

Objective There is a lot of information about cancer in Electronic Health Record (EHR) notes
that can be useful for biomedical research provided natural language processing (NLP) …

Pathology text mining is a challenging task given the reporting variability and constant new
findings in cancer sub-type definitions. However, successful text mining of a large pathology …

Pathology reports primarily consist of unstructured free text and thus the clinical information
contained in the reports is not trivial to access or query. Multiple natural language …

Integrating large language models (LLMs) to retrieve targeted medical knowledge from
electronic health records enables significant advancements in medical research. However …

PURPOSE Clinicians need accurate and timely information on the impact of treatments on
patient outcomes. The electronic health record (EHR) offers the potential for insight into real …

Objective Cancer is a leading cause of death, but much of the diagnostic information is
stored as unstructured data in pathology reports. We aim to improve uncertainty estimates of …

Background Surveillance recommendations for patients with low‐risk, non–muscle‐invasive
bladder cancer (NMIBC) are based on limited evidence. The objective of this study was to …

INTRODUCTION The use of artificial intelligence (AI) in urology is gaining significant
traction. While previous reviews of AI applications in urology exist, there have been few …

Background Accurate identification of new diagnoses of human papillomavirus–associated
cancers and precancers is an important step toward the development of strategies that …