Using Artificial Intelligence in Fungal Lung Disease: CPA CT Imaging as an Example

被引：7
作者：
Angelini, Elsa [1 ,2 ]
Shah, Anand [3 ,4 ]
机构：
[1] Imperial Coll London, NIHR Imperial Biomed Res Ctr, ITMAT Data Sci Grp, London, England
[2] Imperial Coll London, Dept Metab Digest Reprod, London, England
[3] Royal Brompton & Harefield NHS Fdn Trust, Resp Med, London, England
[4] Imperial Coll London, MRC Ctr Global Infect Dis Anal, Sch Publ Hlth, Dept Infect Dis Epidemiol, London, England
来源：
MYCOPATHOLOGIA | 2021年 / 186卷 / 05期
关键词：
Chronic pulmonary aspergillosis (CPA); CT imaging; Artificial intelligence (AI); ASPERGILLOSIS; DIAGNOSIS; MANAGEMENT;
D O I：
10.1007/s11046-021-00546-0
中图分类号：
Q93 [微生物学];
学科分类号：
071005 ; 100705 ;
摘要：
This positioning paper aims to discuss current challenges and opportunities for artificial intelligence (AI) in fungal lung disease, with a focus on chronic pulmonary aspergillosis and some supporting proof-of-concept results using lung imaging. Given the high uncertainty in fungal infection diagnosis and analyzing treatment response, AI could potentially have an impactful role; however, developing imaging-based machine learning raises several specific challenges. We discuss recommendations to engage the medical community in essential first steps towards fungal infection AI with gathering dedicated imaging registries, linking with non-imaging data and harmonizing image-finding annotations.
引用
收藏
页码：733 / 737
页数：5
相关论文
共 30 条
  • [1] Angelini E, IEEE INT S BIOM IM I
  • [2] Chronic pulmonary aspergillosis update: A year in review
    Barac, Aleksandra
    Kosmidis, Chris
    Alastruey-Izquierdo, Ana
    Salzer, Helmut J. F.
    [J]. MEDICAL MYCOLOGY, 2019, 57 : S104 - S109
  • [3] Invasive mould infections in the ICU setting: complexities and solutions
    Bassetti, Matteo
    Bouza, Emilio
    [J]. JOURNAL OF ANTIMICROBIAL CHEMOTHERAPY, 2017, 72 : I39 - I47
  • [4] Assessing Radiology Research on Artificial Intelligence: A Brief Guide for Authors, Reviewers, and Readers-From the Radiology Editorial Board
    Bluemke, David A.
    Moy, Linda
    Bredella, Miriam A.
    Ertl-Wagner, Birgit B.
    Fowler, Kathryn J.
    Goh, Vicky J.
    Halpern, Elkan F.
    Hess, Christopher P.
    Schiebler, Mark L.
    Weiss, Clifford R.
    [J]. RADIOLOGY, 2020, 294 (03) : 487 - 489
  • [5] Twelve-month clinical outcomes of 206 patients with chronic pulmonary aspergillosis
    Bongomin, Felix
    Harris, Chris
    Hayes, Gemma
    Kosmidis, Chris
    Denning, David W.
    [J]. PLOS ONE, 2018, 13 (04):
  • [6] Bongomin F, 2017, J FUNGI, V3, DOI [10.3390/jof3020026, 10.3390/jof3040057]
  • [7] Towards automatic pulmonary nodule management in lung cancer screening with deep learning
    Ciompi, Francesco
    Chung, Kaman
    van Riel, Sarah J.
    Setio, Arnaud Arindra Adiyoso
    Gerke, Paul K.
    Jacobs, Colin
    Scholten, Ernst Th.
    Schaefer-Prokop, Cornelia
    Wille, Mathilde M. W.
    Marchiano, Alfonso
    Pastorino, Ugo
    Prokop, Mathias
    van Ginneken, Bram
    [J]. SCIENTIFIC REPORTS, 2017, 7
  • [8] Collins GS, 2015, ANN INTERN MED, V162, P55, DOI [10.7326/M14-0697, 10.1016/j.jclinepi.2014.11.010, 10.1186/s12916-014-0241-z, 10.1038/bjc.2014.639, 10.7326/M14-0698, 10.1002/bjs.9736, 10.1136/bmj.g7594, 10.1016/j.eururo.2014.11.025]
  • [9] Chronic pulmonary aspergillosis: rationale and clinical guidelines for diagnosis and management
    Denning, David W.
    Cadranel, Jacques
    Beigelman-Aubry, Catherine
    Ader, Florence
    Chakrabarti, Arunaloke
    Blot, Stijn
    Ullmann, Andrew J.
    Dimopoulos, George
    Lange, Christoph
    [J]. EUROPEAN RESPIRATORY JOURNAL, 2016, 47 (01) : 45 - 68
  • [10] Identification of potentially undiagnosed patients with nontuberculous mycobacteria lung disease using machine learning applied to primary care data in the UK
    Doyle, Orla M.
    van der Laan, Roald
    Obradovic, Marko
    McMahon, Peter
    Daniels, Flora
    Pitcher, Ashley
    Loebinger, Michael R.
    [J]. EUROPEAN RESPIRATORY JOURNAL, 2020, 56 (04)
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