207 related articles for article (PubMed ID: 34383673)
1. Ranking Rule-Based Automatic Explanations for Machine Learning Predictions on Asthma Hospital Encounters in Patients With Asthma: Retrospective Cohort Study.
Zhang X; Luo G
JMIR Med Inform; 2021 Aug; 9(8):e28287. PubMed ID: 34383673
[TBL] [Abstract][Full Text] [Related]
2. Generalizability of an Automatic Explanation Method for Machine Learning Prediction Results on Asthma-Related Hospital Visits in Patients With Asthma: Quantitative Analysis.
Luo G; Nau CL; Crawford WW; Schatz M; Zeiger RS; Koebnick C
J Med Internet Res; 2021 Apr; 23(4):e24153. PubMed ID: 33856359
[TBL] [Abstract][Full Text] [Related]
3. Automatically Explaining Machine Learning Predictions on Severe Chronic Obstructive Pulmonary Disease Exacerbations: Retrospective Cohort Study.
Zeng S; Arjomandi M; Luo G
JMIR Med Inform; 2022 Feb; 10(2):e33043. PubMed ID: 35212634
[TBL] [Abstract][Full Text] [Related]
4. Testing the Generalizability of an Automated Method for Explaining Machine Learning Predictions on Asthma Patients' Asthma Hospital Visits to an Academic Healthcare System.
Tong Y; Messinger AI; Luo G
IEEE Access; 2020; 8():195971-195979. PubMed ID: 33240737
[TBL] [Abstract][Full Text] [Related]
5. Automatically Explaining Machine Learning Prediction Results on Asthma Hospital Visits in Patients With Asthma: Secondary Analysis.
Luo G; Johnson MD; Nkoy FL; He S; Stone BL
JMIR Med Inform; 2020 Dec; 8(12):e21965. PubMed ID: 33382379
[TBL] [Abstract][Full Text] [Related]
6. Forecasting Future Asthma Hospital Encounters of Patients With Asthma in an Academic Health Care System: Predictive Model Development and Secondary Analysis Study.
Tong Y; Messinger AI; Wilcox AB; Mooney SD; Davidson GH; Suri P; Luo G
J Med Internet Res; 2021 Apr; 23(4):e22796. PubMed ID: 33861206
[TBL] [Abstract][Full Text] [Related]
7. A Roadmap for Automating Lineage Tracing to Aid Automatically Explaining Machine Learning Predictions for Clinical Decision Support.
Luo G
JMIR Med Inform; 2021 May; 9(5):e27778. PubMed ID: 34042600
[TBL] [Abstract][Full Text] [Related]
8. Using Temporal Features to Provide Data-Driven Clinical Early Warnings for Chronic Obstructive Pulmonary Disease and Asthma Care Management: Protocol for a Secondary Analysis.
Luo G; Stone BL; Koebnick C; He S; Au DH; Sheng X; Murtaugh MA; Sward KA; Schatz M; Zeiger RS; Davidson GH; Nkoy FL
JMIR Res Protoc; 2019 Jun; 8(6):e13783. PubMed ID: 31199308
[TBL] [Abstract][Full Text] [Related]
9. Developing a Predictive Model for Asthma-Related Hospital Encounters in Patients With Asthma in a Large, Integrated Health Care System: Secondary Analysis.
Luo G; Nau CL; Crawford WW; Schatz M; Zeiger RS; Rozema E; Koebnick C
JMIR Med Inform; 2020 Nov; 8(11):e22689. PubMed ID: 33164906
[TBL] [Abstract][Full Text] [Related]
10. Developing a Model to Predict Hospital Encounters for Asthma in Asthmatic Patients: Secondary Analysis.
Luo G; He S; Stone BL; Nkoy FL; Johnson MD
JMIR Med Inform; 2020 Jan; 8(1):e16080. PubMed ID: 31961332
[TBL] [Abstract][Full Text] [Related]
11. Error and Timeliness Analysis for Using Machine Learning to Predict Asthma Hospital Visits: Retrospective Cohort Study.
Zhang X; Luo G
JMIR Med Inform; 2022 Jun; 10(6):e38220. PubMed ID: 35675129
[TBL] [Abstract][Full Text] [Related]
12. A qualitative research framework for the design of user-centered displays of explanations for machine learning model predictions in healthcare.
Barda AJ; Horvat CM; Hochheiser H
BMC Med Inform Decis Mak; 2020 Oct; 20(1):257. PubMed ID: 33032582
[TBL] [Abstract][Full Text] [Related]
13. Using a Constraint-Based Method to Identify Chronic Disease Patients Who Are Apt to Obtain Care Mostly Within a Given Health Care System: Retrospective Cohort Study.
Tong Y; Liao ZC; Tarczy-Hornoch P; Luo G
JMIR Form Res; 2021 Oct; 5(10):e26314. PubMed ID: 34617906
[TBL] [Abstract][Full Text] [Related]
14. Using Computational Methods to Improve Integrated Disease Management for Asthma and Chronic Obstructive Pulmonary Disease: Protocol for a Secondary Analysis.
Luo G; Stone BL; Sheng X; He S; Koebnick C; Nkoy FL
JMIR Res Protoc; 2021 May; 10(5):e27065. PubMed ID: 34003134
[TBL] [Abstract][Full Text] [Related]
15. A Mobile App That Addresses Interpretability Challenges in Machine Learning-Based Diabetes Predictions: Survey-Based User Study.
Hendawi R; Li J; Roy S
JMIR Form Res; 2023 Nov; 7():e50328. PubMed ID: 37955948
[TBL] [Abstract][Full Text] [Related]
16. Explainable Machine Learning Framework for Image Classification Problems: Case Study on Glioma Cancer Prediction.
Pintelas E; Liaskos M; Livieris IE; Kotsiantis S; Pintelas P
J Imaging; 2020 May; 6(6):. PubMed ID: 34460583
[TBL] [Abstract][Full Text] [Related]
17. Using Automated Machine Learning to Predict the Mortality of Patients With COVID-19: Prediction Model Development Study.
Ikemura K; Bellin E; Yagi Y; Billett H; Saada M; Simone K; Stahl L; Szymanski J; Goldstein DY; Reyes Gil M
J Med Internet Res; 2021 Feb; 23(2):e23458. PubMed ID: 33539308
[TBL] [Abstract][Full Text] [Related]
18. Automatically explaining machine learning prediction results: a demonstration on type 2 diabetes risk prediction.
Luo G
Health Inf Sci Syst; 2016; 4():2. PubMed ID: 26958341
[TBL] [Abstract][Full Text] [Related]
19. Predictive Modeling of 30-Day Emergency Hospital Transport of Patients Using a Personal Emergency Response System: Prognostic Retrospective Study.
Op den Buijs J; Simons M; Golas S; Fischer N; Felsted J; Schertzer L; Agboola S; Kvedar J; Jethwani K
JMIR Med Inform; 2018 Nov; 6(4):e49. PubMed ID: 30482741
[TBL] [Abstract][Full Text] [Related]
20. Development of a Computable Phenotype for Prehospital Pediatric Asthma Encounters.
Harmon I; Brailsford J; Sanchez-Cano I; Fishe J
Prehosp Emerg Care; 2024 May; ():1-12. PubMed ID: 38713633
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
