Classifying Asthma Health Deterioration Using Synthetic Patient Data Generation and Associated Machine-learning Predictions Derived From Global Clinical Characteristic Data

被引：0
|
作者：
Iyer, S. [1 ]
Swaminathan, S. [2 ]
Landon, C. [3 ]
Wysham, N. [4 ]
Ramanathan, S. [2 ]
Toro, B. [2 ]
Naseer, A. [5 ]
机构：
[1] Vironix, Austin, TX USA
[2] Vironix Hlth, Austin, TX USA
[3] Ventura Cty Med Ctr, Ventura, CA USA
[4] Vancouver Clin, 3750 NE Davis, Portland, OR USA
[5] Univ Oxford, Oxford, England
来源：
AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE | 2023年 / 207卷
关键词：
D O I：
暂无
中图分类号：
R4 [临床医学];
学科分类号：
1002 ; 100602 ;
摘要：
A1415
引用
收藏
页数：2
相关论文
共 16 条
  • [1] Early prediction of clinical deterioration using data-driven machine-learning modeling of electronic health records
    Ruiz, Victor M.
    Goldsmith, Michael P.
    Shi, Lingyun
    Simpao, Allan F.
    Galvez, Jorge A.
    Naim, Maryam Y.
    Nadkarni, Vinay
    Gaynor, J. William
    Tsui, Fuchiang
    [J]. JOURNAL OF THORACIC AND CARDIOVASCULAR SURGERY, 2022, 164 (01): : 211 - +
  • [2] Importance of GWAS Risk Loci and Clinical Data in Predicting Asthma Using Machine-learning Approaches
    Qin, Zan-Mei
    Liang, Si-Qiao
    Long, Jian-Xiong
    Deng, Jing-Min
    Wei, Xuan
    Yang, Mei-Ling
    Tang, Shao-Jie
    Li, Hai-Li
    [J]. COMBINATORIAL CHEMISTRY & HIGH THROUGHPUT SCREENING, 2024, 27 (03) : 400 - 407
  • [3] Simulation of a machine learning enabled learning health system for risk prediction using synthetic patient data
    Chen, Anjun
    Chen, Drake O.
    [J]. SCIENTIFIC REPORTS, 2022, 12 (01)
  • [4] Simulation of a machine learning enabled learning health system for risk prediction using synthetic patient data
    Anjun Chen
    Drake O. Chen
    [J]. Scientific Reports, 12
  • [5] Early Prediction of Neonatal Sepsis From Synthetic Clinical Data Using Machine Learning
    Lyra, Simon
    Jin, Jinyi
    Leonhardt, Steffen
    Lueken, Markus
    [J]. 2023 45TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE & BIOLOGY SOCIETY, EMBC, 2023,
  • [6] Herbage biomass predictions from UAV data using a derived digital terrain model and machine learning
    Aebischer, Philippe
    Sutter, Michael
    Birkinshaw, Amy
    Nussbaum, Madlene
    Reidy, Beat
    [J]. GRASS AND FORAGE SCIENCE, 2024,
  • [7] Using Electronic Health Records and Machine Learning to Make Medical-Related Predictions from Non-Medical Data
    Pitoglou, Stavros
    Koumpouros, Yiannis
    Anastasiou, Athanasios
    [J]. 2018 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND DATA ENGINEERING (ICMLDE 2018), 2018, : 56 - 60
  • [8] Uncertainty assessment in unsupervised machine-learning methods for deepwater channel seismic facies using outcrop-derived 3D models and synthetic seismic data
    La Marca, Karelia
    Bedle, Heather
    Stright, Lisa
    Marfurt, Kurt
    [J]. INTERPRETATION-A JOURNAL OF SUBSURFACE CHARACTERIZATION, 2024, 12 (03): : T303 - T319
  • [9] Clinical and psychological factors associated with resilience in patients with schizophrenia: data from the Italian network for research on psychoses using machine learning
    Antonucci, Linda A.
    Pergola, Giulio
    Rampino, Antonio
    Rocca, Paola
    Rossi, Alessandro
    Amore, Mario
    Aguglia, Eugenio
    Bellomo, Antonello
    Bianchini, Valeria
    Brasso, Claudio
    Bucci, Paola
    Carpiniello, Bernardo
    Dell'Osso, Liliana
    di Fabio, Fabio
    di Giannantonio, Massimo
    Fagiolini, Andrea
    Giordano, Giulia Maria
    Marcatilli, Matteo
    Marchesi, Carlo
    Meneguzzo, Paolo
    Monteleone, Palmiero
    Pompili, Maurizio
    Rossi, Rodolfo
    Siracusano, Alberto
    Vita, Antonio
    Zeppegno, Patrizia
    Galderisi, Silvana
    Bertolino, Alessandro
    Maj, Mario
    [J]. PSYCHOLOGICAL MEDICINE, 2023, 53 (12) : 5717 - 5728
  • [10] Using Machine Learning to Determine Variable Predictors of Exacerbation and Predict Patient-Level Occurrence of Exacerbation from Screening and Baseline Clinical Data
    Mofor, E.
    Arcadu, F.
    Brizzi, F.
    Soubret, A.
    Tew, W.
    Cheung, D. S.
    Olsson, J. K.
    Lin, S.
    Prunotto, M.
    [J]. AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE, 2020, 201
12