This paper is in the following e-collection/theme issue:

Machine Learning (1385)

Published on in Vol 5, No 3 (2017): Jul-Sept

A Roadmap for Optimizing Asthma Care Management via Computational Approaches

A Roadmap for Optimizing Asthma Care Management via Computational Approaches

A Roadmap for Optimizing Asthma Care Management via Computational Approaches

Authors of this article:

Gang Luo1 Author Orcid Image ;   Katherine Sward2 Author Orcid Image
Article Authors Cited by (12) Tweetations (4) Metrics

Journals

  1. Roe K, Jawa V, Zhang X, Chute C, Epstein J, Matelsky J, Shpitser I, Taylor C, Uzuner O. Feature engineering with clinical expert knowledge: A case study assessment of machine learning model complexity and performance. PLOS ONE 2020;15(4):e0231300 View
  2. Luo G. A roadmap for semi-automatically extracting predictive and clinically meaningful temporal features from medical data for predictive modeling. Global Transitions 2019;1:61 View
  3. Zeng X, Luo G. Progressive sampling-based Bayesian optimization for efficient and automatic machine learning model selection. Health Information Science and Systems 2017;5(1) View
  4. Rankin D, Black M, Bond R, Wallace J, Mulvenna M, Epelde G. Reliability of Supervised Machine Learning Using Synthetic Data in Health Care: Model to Preserve Privacy for Data Sharing. JMIR Medical Informatics 2020;8(7):e18910 View
  5. Luo G, He S, Stone B, Nkoy F, Johnson M. Developing a Model to Predict Hospital Encounters for Asthma in Asthmatic Patients: Secondary Analysis. JMIR Medical Informatics 2020;8(1):e16080 View
  6. Luo G, Stone B, Koebnick C, He S, Au D, Sheng X, Murtaugh M, Sward K, Schatz M, Zeiger R, Davidson G, Nkoy F. Using Temporal Features to Provide Data-Driven Clinical Early Warnings for Chronic Obstructive Pulmonary Disease and Asthma Care Management: Protocol for a Secondary Analysis. JMIR Research Protocols 2019;8(6):e13783 View
  7. Luo G, Stone B, Sheng X, He S, Koebnick C, Nkoy F. Using Computational Methods to Improve Integrated Disease Management for Asthma and Chronic Obstructive Pulmonary Disease: Protocol for a Secondary Analysis. JMIR Research Protocols 2021;10(5):e27065 View
  8. Kennedy K, Allenbrand R, Bowles E. The Role of Home Environments in Allergic Disease. Clinical Reviews in Allergy & Immunology 2019;57(3):364 View
  9. Ekpo R, Osamor V, Azeta A, Ikeakanam E, Amos B. Machine learning classification approach for asthma prediction models in children. Health and Technology 2023;13(1):1 View
  10. Meng Z, Chen H, Deng C, Meng S. Potential cellular endocrinology mechanisms underlying the effects of Chinese herbal medicine therapy on asthma. Frontiers in Endocrinology 2022;13 View
  11. Luo G. A Roadmap for Boosting Model Generalizability for Predicting Hospital Encounters for Asthma. JMIR Medical Informatics 2022;10(3):e33044 View
  12. Bae W, Alkobaisi S, Horak M, Park C, Kim S, Davidson J. Predicting Health Risks of Adult Asthmatics Susceptible to Indoor Air Quality Using Improved Logistic and Quantile Regression Models. Life 2022;12(10):1631 View