Medical imaging is a key component in clinical diagnosis, treatment planning and clinical
trial design, accounting for almost 90% of all healthcare data. CNNs achieved performance …

Purpose To train a deep natural language processing (NLP) model, using data mined
structured oncology reports (SOR), for rapid tumor response category (TRC) classification …

Ali S. Tejani, MD, is a radiology resident at the University of Texas Southwestern Medical
Center in Dallas, Tex, where he founded the Imaging Informatics and Business Intelligence …

Natural language processing is an exciting and emerging field in health care that can
transform the field of orthopaedics. It can aid in the process of automated clinical data …

Objective Textual radiology reports contain a wealth of information that may help understand
associations among diseases and imaging observations. This study evaluated the ability to …

Objectives To assess radiologists' current use of, and opinions on, structured reporting (SR)
in oncologic imaging, and to provide recommendations for a structured report template …

This paper describes the Radiology Report TNM staging (RR-TNM) subtask as a part of
NTCIR-17 Medical Natural Language Processing for Social Media and Clinical Texts …

Purpose Natural language processing using language models has yielded promising results
in various fields. Language models can help improve the workflow of radiologists. This …

Background Radiology reports are typically written in a free-text format, making clinical
information difficult to extract and use. Recently, the adoption of structured reporting (SR) …

Mobile health apps are widely used for breast cancer detection using artificial intelligence
algorithms, providing radiologists with second opinions and reducing false diagnoses. This …