NTM-Lung Disease: Machine Learning identifies undiagnosed Patients

被引:0
|
作者
Manych, Matthias
机构
来源
PNEUMOLOGIE | 2020年 / 74卷 / 12期
关键词
D O I
10.1055/a-1210-5352
中图分类号
R56 [呼吸系及胸部疾病];
学科分类号
摘要
Die nichttuberkulose mykobakterielle (NTM) Lungenerkrankung ist insgesamt selten, ihre Inzidenz und Pravalenz nehmen aber zu. Aktuell wird die jahrliche Pravalenz in Europa auf 3,3-6 Falle pro 100000 geschatzt. Die Identifizierung von Patienten mit NTM-Lungenerkrankung konnte durch die Anwendung kunstlicher Intelligenz (KI) verbessert werden, wie eine Studie fur das United Kingdom belegt.
引用
收藏
页数:1
相关论文
共 50 条
  • [1] PRE-OPERATIVE SPIROMETRY IDENTIFIES UNDIAGNOSED LUNG DISEASE IN CARDIAC PATIENTS
    Peat, R.
    Town, S.
    Hawkes, S.
    Price, D.
    Frost, F.
    Wat, D.
    THORAX, 2019, 74 : A160 - A160
  • [2] Machine Learning in Detection of Undiagnosed Celiac Disease
    Hujoel, Isabel A.
    Murphree, Dennis H., Jr.
    Van Dyke, Carol T.
    Choung, Rok Seon
    Sharma, Ayush
    Murray, Joseph A.
    Rubio-Tapia, Alberto
    CLINICAL GASTROENTEROLOGY AND HEPATOLOGY, 2018, 16 (08) : 1354 - +
  • [3] 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.
    EUROPEAN RESPIRATORY JOURNAL, 2020, 56 (04)
  • [4] Validation of the Nontuberculous Mycobacteria (NTM) Module in NTM Lung Disease
    Deshpande, Chinmay
    Quittner, Alexandra
    Chou, Engels
    Shah, Ruchit
    Bose, Srimoyee
    Lasch, Kathy
    Zhang, Quan
    EUROPEAN RESPIRATORY JOURNAL, 2018, 52
  • [5] IDENTIFICATION OF POTENTIALLY UNDIAGNOSED PATIENTS WITH NON-TUBERCULOUS MYCOBACTERIAL LUNG DISEASE USING MACHINE LEARNING APPLIED TO PRIMARY CARE DATA IN UK
    Doyle, O. M.
    McMahon, P.
    Daniels, F.
    Pitcher, A.
    Obradovic, M.
    Van der Laan, R.
    Loebinger, M.
    VALUE IN HEALTH, 2019, 22 : S879 - S879
  • [6] Machine Learning Identifies Predicators of Disease-Free Survival in Patients with Cervical Cancer
    Yoshida, E.
    Gonzalez, W. Arbelo
    Valdes, G.
    Hirata, E.
    Morin, O.
    Hsu, I.
    RADIOTHERAPY AND ONCOLOGY, 2021, 161 : S1068 - S1069
  • [7] Management of Nontuberculous Mycobacterial (NTM) Lung Disease
    Philley, Julie V.
    Griffith, David E.
    SEMINARS IN RESPIRATORY AND CRITICAL CARE MEDICINE, 2013, 34 (01) : 135 - 142
  • [8] Clinical Characteristics And Outcomes Of Ntm Lung Disease In Patients Treated With Tnf Antagonist
    Yang, J.
    Yoo, J. -W.
    Jo, K. -W.
    Kang, B. -H.
    Shim, T.
    AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE, 2014, 189
  • [9] A Comparative Analysis of Machine Learning Models for the Detection of Undiagnosed Diabetes Patients
    Cichosz, Simon Lebech
    Bender, Clara
    Hejlesen, Ole
    DIABETOLOGY, 2024, 5 (01): : 1 - 11
  • [10] The Impact of Genomic Classifier in Patients With Undiagnosed Interstitial Lung Disease
    Barrera, D. Espinoza
    Alanis, R. Villalobos
    Becnel, D.
    Abdelghani, R.
    Kheir, F.
    AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE, 2023, 207