These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
631 related articles for article (PubMed ID: 37277767)
1. Interpretable machine learning models for hospital readmission prediction: a two-step extracted regression tree approach. Gao X; Alam S; Shi P; Dexter F; Kong N BMC Med Inform Decis Mak; 2023 Jun; 23(1):104. PubMed ID: 37277767 [TBL] [Abstract][Full Text] [Related]
2. Predictive modeling for 14-day unplanned hospital readmission risk by using machine learning algorithms. Lo YT; Liao JC; Chen MH; Chang CM; Li CT BMC Med Inform Decis Mak; 2021 Oct; 21(1):288. PubMed ID: 34670553 [TBL] [Abstract][Full Text] [Related]
3. Building interpretable predictive models for pediatric hospital readmission using Tree-Lasso logistic regression. Jovanovic M; Radovanovic S; Vukicevic M; Van Poucke S; Delibasic B Artif Intell Med; 2016 Sep; 72():12-21. PubMed ID: 27664505 [TBL] [Abstract][Full Text] [Related]
4. Evaluating machine learning algorithms to Predict 30-day Unplanned REadmission (PURE) in Urology patients. Welvaars K; van den Bekerom MPJ; Doornberg JN; van Haarst EP; BMC Med Inform Decis Mak; 2023 Jun; 23(1):108. PubMed ID: 37312177 [TBL] [Abstract][Full Text] [Related]
5. Using machine learning to predict paediatric 30-day unplanned hospital readmissions: a case-control retrospective analysis of medical records, including written discharge documentation. Zhou H; Albrecht MA; Roberts PA; Porter P; Della PR Aust Health Rev; 2021 Jun; 45(3):328-337. PubMed ID: 33840419 [TBL] [Abstract][Full Text] [Related]
6. The Price of Explainability in Machine Learning Models for 100-Day Readmission Prediction in Heart Failure: Retrospective, Comparative, Machine Learning Study. Soliman A; Agvall B; Etminani K; Hamed O; Lingman M J Med Internet Res; 2023 Oct; 25():e46934. PubMed ID: 37889530 [TBL] [Abstract][Full Text] [Related]
7. Development and validation of an interpretable 3 day intensive care unit readmission prediction model using explainable boosting machines. Hegselmann S; Ertmer C; Volkert T; Gottschalk A; Dugas M; Varghese J Front Med (Lausanne); 2022; 9():960296. PubMed ID: 36082270 [TBL] [Abstract][Full Text] [Related]
8. Machine learning-based prediction of heart failure readmission or death: implications of choosing the right model and the right metrics. Awan SE; Bennamoun M; Sohel F; Sanfilippo FM; Dwivedi G ESC Heart Fail; 2019 Apr; 6(2):428-435. PubMed ID: 30810291 [TBL] [Abstract][Full Text] [Related]
9. A hospital wide predictive model for unplanned readmission using hierarchical ICD data. Deschepper M; Eeckloo K; Vogelaers D; Waegeman W Comput Methods Programs Biomed; 2019 May; 173():177-183. PubMed ID: 30777619 [TBL] [Abstract][Full Text] [Related]
10. How Good Is Machine Learning in Predicting All-Cause 30-Day Hospital Readmission? Evidence From Administrative Data. Li Q; Yao X; Échevin D Value Health; 2020 Oct; 23(10):1307-1315. PubMed ID: 33032774 [TBL] [Abstract][Full Text] [Related]
11. Machine learning methods to predict 30-day hospital readmission outcome among US adults with pneumonia: analysis of the national readmission database. Huang Y; Talwar A; Lin Y; Aparasu RR BMC Med Inform Decis Mak; 2022 Nov; 22(1):288. PubMed ID: 36352392 [TBL] [Abstract][Full Text] [Related]
12. Application of machine learning in predicting hospital readmissions: a scoping review of the literature. Huang Y; Talwar A; Chatterjee S; Aparasu RR BMC Med Res Methodol; 2021 May; 21(1):96. PubMed ID: 33952192 [TBL] [Abstract][Full Text] [Related]
15. Machine Learning to Predict Outcomes and Cost by Phase of Care After Coronary Artery Bypass Grafting. Zea-Vera R; Ryan CT; Havelka J; Corr SJ; Nguyen TC; Chatterjee S; Wall MJ; Coselli JS; Rosengart TK; Ghanta RK Ann Thorac Surg; 2022 Sep; 114(3):711-719. PubMed ID: 34582751 [TBL] [Abstract][Full Text] [Related]
16. Predictive models for hospital readmission risk: A systematic review of methods. Artetxe A; Beristain A; Graña M Comput Methods Programs Biomed; 2018 Oct; 164():49-64. PubMed ID: 30195431 [TBL] [Abstract][Full Text] [Related]
17. Improving Clinical Translation of Machine Learning Approaches Through Clinician-Tailored Visual Displays of Black Box Algorithms: Development and Validation. Wongvibulsin S; Wu KC; Zeger SL JMIR Med Inform; 2020 Jun; 8(6):e15791. PubMed ID: 32515746 [TBL] [Abstract][Full Text] [Related]
18. IHCP: interpretable hepatitis C prediction system based on black-box machine learning models. Fan Y; Lu X; Sun G BMC Bioinformatics; 2023 Sep; 24(1):333. PubMed ID: 37674125 [TBL] [Abstract][Full Text] [Related]
19. 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]
20. Neural networks versus Logistic regression for 30 days all-cause readmission prediction. Allam A; Nagy M; Thoma G; Krauthammer M Sci Rep; 2019 Jun; 9(1):9277. PubMed ID: 31243311 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]