Deep learning to convert unstructured CT pulmonary angiography reports into structured reports

被引：0
|
作者：
Adam Spandorfer
Cody Branch
Puneet Sharma
Pooyan Sahbaee
U. Joseph Schoepf
James G. Ravenel
John W. Nance
机构：
[1] Medical University of South Carolina,Department of Radiology
[2] Siemens Medical Solutions USA,undefined
[3] Inc.,undefined
来源：
European Radiology Experimental | / 3卷
关键词：
Artificial intelligence; Machine learning; Natural language processing; Structured reporting; Tomography (x-ray, computed);
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
相关论文
共 50 条
  • [31] A deep learning approach for automated diagnosis of pulmonary embolism on computed tomographic pulmonary angiography
    Pranav Ajmera
    Amit Kharat
    Jitesh Seth
    Snehal Rathi
    Richa Pant
    Manish Gawali
    Viraj Kulkarni
    Ragamayi Maramraju
    Isha Kedia
    Rajesh Botchu
    Sanjay Khaladkar
    BMC Medical Imaging, 22
  • [32] Predicting decompression surgery by applying multimodal deep learning to patients’ structured and unstructured health data
    Chethan Jujjavarapu
    Pradeep Suri
    Vikas Pejaver
    Janna Friedly
    Laura S. Gold
    Eric Meier
    Trevor Cohen
    Sean D. Mooney
    Patrick J. Heagerty
    Jeffrey G. Jarvik
    BMC Medical Informatics and Decision Making, 23
  • [33] Predicting decompression surgery by applying multimodal deep learning to patients' structured and unstructured health data
    Jujjavarapu, Chethan
    Suri, Pradeep
    Pejaver, Vikas
    Friedly, Janna
    Gold, Laura S.
    Meier, Eric
    Cohen, Trevor
    Mooney, Sean D.
    Heagerty, Patrick J.
    Jarvik, Jeffrey G.
    BMC MEDICAL INFORMATICS AND DECISION MAKING, 2023, 23 (01)
  • [34] Enhancing Radiological Reporting in Head and Neck Cancer: Converting Free-Text CT Scan Reports to Structured Reports Using Large Language Models
    Gupta, Amit
    Malhotra, Hema
    Garg, Amit K.
    Rangarajan, Krithika
    INDIAN JOURNAL OF RADIOLOGY AND IMAGING, 2025, 35 (01) : 43 - 49
  • [35] Deep learning–based image restoration algorithm for coronary CT angiography
    Fuminari Tatsugami
    Toru Higaki
    Yuko Nakamura
    Zhou Yu
    Jian Zhou
    Yujie Lu
    Chikako Fujioka
    Toshiro Kitagawa
    Yasuki Kihara
    Makoto Iida
    Kazuo Awai
    European Radiology, 2019, 29 : 5322 - 5329
  • [36] Contextualizing injury severity from occupational accident reports using an optimized deep learning prediction model
    Khairuddin, Mohamed Zul Fadhli
    Sankaranarayanan, Suresh
    Hasikin, Khairunnisa
    Razak, Nasrul Anuar Abd
    Omar, Rosidah
    PEERJ COMPUTER SCIENCE, 2024, 10
  • [37] Comparison of deep learning models for natural language processing-based classification of non-English head CT reports
    Barash, Yiftach
    Guralnik, Gennadiy
    Tau, Noam
    Soffer, Shelly
    Levy, Tal
    Shimon, Orit
    Zimlichman, Eyal
    Konen, Eli
    Klang, Eyal
    NEURORADIOLOGY, 2020, 62 (10) : 1247 - 1256
  • [38] Deep Learning for Automated Extraction of Primary Sites From Cancer Pathology Reports
    Qiu, John X.
    Yoon, Hong-Jun
    Fearn, Paul A.
    Tourassi, Georgia D.
    IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2018, 22 (01) : 244 - 251
  • [39] Segmentation of acute pulmonary embolism in computed tomography pulmonary angiography using the deep learning method
    Aydin, Nevin
    Cihan, Cagatay
    Celik, Ozer
    Aslan, Ahmet Faruk
    Odabas, Alper
    Alatas, Fusun
    Yildirim, Huseyin
    TUBERKULOZ VE TORAKS-TUBERCULOSIS AND THORAX, 2023, 71 (02): : 131 - 137
  • [40] Computer-Aided Diagnosis of Pulmonary Fibrosis Using Deep Learning and CT Images
    Christe, Andreas
    Peters, Alan A.
    Drakopoulos, Dionysios
    Heverhagen, Johannes T.
    Geiser, Thomas
    Stathopoulou, Thomai
    Christodoulidis, Stergios
    Anthimopoulos, Marios
    Mougiakakou, Stavroula G.
    Ebner, Lukas
    INVESTIGATIVE RADIOLOGY, 2019, 54 (10) : 627 - 632
12345