A comprehensive bedside chest radiography dataset with structured, itemized and graded radiologic reports

Scientific Data, vol. 13

Abstract

Automated analysis of bedside chest radiographs remains challenging due to limited large-scale datasets with expert annotations and standardized severity grading. We provide TAIX-Ray, a comprehensive dataset of 215,381 bedside chest radiographs collected from 47,724 intensive care unit patients (30,306 male, 17,418 female, median age 68 years) collected over 14 years (01/2010-12/2023) at the University Hospital Aachen, Germany. During routine clinical reporting, 134 trained radiologists provided structured, itemized reports using a standardized template. They systematically assessed eight pathological findings: heart size (cardiomegaly), pulmonary congestion, pleural effusion (left/right), pulmonary opacities (left/right), and atelectasis (left/right) using a five-point ordinal severity scale (absent, questionable, mild, moderate, severe). The dataset includes (i) bedside chest radiographs (anteroposterior projections), (ii) structured, itemized reports, (iii) patient demographics (age and sex), and (iv) the temporal metadata. To facilitate immediate research adoption, we provide a baseline transformer model, implementation code, and predefined data splits, ensuring reproducible benchmarking. This resource enables the development of clinical AI models for automated pathology detection and severity assessment in critical care settings.

Authors 8

1. Daniel Truhn corresponding Aachen Department of Diagnostic and Interventional Radiology

   Universitätsklinikum Aachen · RWTH Aachen University

   Affiliation as printed

   Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany. dtruhn@ukaachen.de

2. Robert Malte Siepmann Aachen Department of Diagnostic and Interventional Radiology

   Universitätsklinikum Aachen · RWTH Aachen University

   Affiliation as printed

   Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany

3. Marc Sebastian von der Stück Aachen Department of Diagnostic and Interventional Radiology

   Universitätsklinikum Aachen · RWTH Aachen University

   Affiliation as printed

   Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany

4. Keno K. Bressem

   TUM Klinikum · Deutsches Herzzentrum München · Technical University of Munich

   Affiliation as printed

   Department of Cardiovascular Radiology and Nuclear Medicine, Technical University of Munich, School of Medicine and Health, German Heart Center, TUM University Hospital, Munich, Germany

   Department of Diagnostic and Interventional Radiology, Technical University of Munich, School of Medicine and Health, Klinikum rechts der Isar, TUM University Hospital, Munich, Germany

5. Jakob Nikolas Kather

   University Hospital Carl Gustav Carus · Else Kröner Fresenius Center for Digital Health · Technische Universität Dresden

   Affiliation as printed

   Else Kroener Fresenius Center for Digital Health, University Hospital Carl Gustav Carus, Dresden, Germany

   Technical University Dresden, Dresden, Germany

6. C Kuhl Aachen Department of Diagnostic and Interventional Radiology

   Universitätsklinikum Aachen · RWTH Aachen University

   Affiliation as printed

   Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany

7. Gustav Anton Müller‐Franzes Aachen Department of Diagnostic and Interventional Radiology

   Universitätsklinikum Aachen · RWTH Aachen University

   Affiliation as printed

   Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany

8. Sven Nebelung Aachen Department of Diagnostic and Interventional Radiology

   Universitätsklinikum Aachen · RWTH Aachen University

   Affiliation as printed

   Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany