Artificial intelligence: a potential prioritisation tool for chest radiographs with suspected thoracic malignancy

被引:0
|
作者
Hussein, M. A. M. [1 ]
Brozik, J. [1 ]
Hopewell, H. [1 ]
Patel, H. [1 ]
Rasalingham, S. [2 ]
Dillard, L. [3 ]
Morgan, T. Naunton [2 ]
Tappouni, R. [3 ]
Malik, Q. [2 ]
Lucas, E. [2 ]
Das, I. [1 ]
机构
[1] Univ Hosp Leicester NHS Trust, Leicester, Leics, England
[2] Behold Ai Technol Ltd, London, England
[3] Behold Ai Technol Ltd, New York, NY USA
关键词
D O I
暂无
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
58
引用
收藏
页码:S25 / S25
页数:1
相关论文
共 50 条
  • [1] Evaluation of the Performance of an Artificial Intelligence (AI) Algorithm in Detecting Thoracic Pathologies on Chest Radiographs
    Bettinger, Hubert
    Lenczner, Gregory
    Guigui, Jean
    Rotenberg, Luc
    Zerbib, Elie
    Attia, Alexandre
    Vidal, Julien
    Beaumel, Pauline
    DIAGNOSTICS, 2024, 14 (11)
  • [2] Artificial Intelligence for Clinical Interpretation of Bedside Chest Radiographs
    Khader, Firas
    Han, Tianyu
    Mueller-Franzes, Gustav
    Huck, Luisa
    Schad, Philipp
    Keil, Sebastian
    Barzakova, Emona
    Schulze-Hagen, Maximilian
    Pedersoli, Federico
    Schulz, Volkmar
    Zimmermann, Markus
    Nebelung, Lina
    Kather, Jakob
    Hamesch, Karim
    Haarburger, Christoph
    Marx, Gernot
    Stegmaier, Johannes
    Kuhl, Christiane
    Bruners, Philipp
    Nebelung, Sven
    Truhn, Daniel
    RADIOLOGY, 2023, 307 (01)
  • [3] Impact of Confounding Thoracic Tubes and Pleural Dehiscence Extent on Artificial Intelligence Pneumothorax Detection in Chest Radiographs
    Rueckel, Johannes
    Trappmann, Lena
    Schachtner, Balthasar
    Wesp, Philipp
    Hoppe, Boj Friedrich
    Fink, Nicola
    Ricke, Jens
    Dinkel, Julien
    Ingrisch, Michael
    Sabel, Bastian Oliver
    INVESTIGATIVE RADIOLOGY, 2020, 55 (12) : 792 - 798
  • [4] The Potential of Artificial Intelligence to Analyze Chest Radiographs for Signs of COVID-19 Pneumonia COMMENT
    van Ginneken, Bram
    RADIOLOGY, 2021, 299 (01) : E214 - E215
  • [5] The Potential Clinical Utility of an Artificial Intelligence Model for Identification of Vertebral Compression Fractures in Chest Radiographs
    Ghatak, Ankita
    Hillis, James M.
    Mercaldo, Sarah F.
    Newbury-Chaet, Isabella
    Chin, John K.
    Digumarthy, Subba R.
    Rodriguez, Karen
    Muse, Victorine V.
    Andriole, Katherine P.
    Dreyer, Keith J.
    Kalra, Mannudeep K.
    Bizzo, Bernardo C.
    JOURNAL OF THE AMERICAN COLLEGE OF RADIOLOGY, 2025, 22 (02) : 220 - 229
  • [6] The impact of artificial intelligence on the reading times of radiologists for chest radiographs
    Hyun Joo Shin
    Kyunghwa Han
    Leeha Ryu
    Eun-Kyung Kim
    npj Digital Medicine, 6
  • [7] The impact of artificial intelligence on the reading times of radiologists for chest radiographs
    Shin, Hyun Joo
    Han, Kyunghwa
    Ryu, Leeha
    Kim, Eun-Kyung
    NPJ DIGITAL MEDICINE, 2023, 6 (01)
  • [8] Artificial Intelligence-Based Detection of Pneumonia in Chest Radiographs
    Becker, Judith
    Decker, Josua A.
    Roemmele, Christoph
    Kahn, Maria
    Messmann, Helmut
    Wehler, Markus
    Schwarz, Florian
    Kroencke, Thomas
    Scheurig-Muenkler, Christian
    DIAGNOSTICS, 2022, 12 (06)
  • [9] Assessing the role of an artificial intelligence assessment tool for thoracic aorta diameter on routine chest CT
    Graby, John
    Harris, Maredudd
    Jones, Calum
    Waring, Harry
    Lyen, Stephen
    Hudson, Benjamin J.
    Rodrigues, Jonathan Carl Luis
    BRITISH JOURNAL OF RADIOLOGY, 2023, 96 (1151):
  • [10] Use of artificial intelligence in triaging of chest radiographs to reduce radiologists’ workload
    Sung Hyun Yoon
    Sunyoung Park
    Sowon Jang
    Junghoon Kim
    Kyung Won Lee
    Woojoo Lee
    Seungjae Lee
    Gabin Yun
    Kyung Hee Lee
    European Radiology, 2024, 34 : 1094 - 1103