163 related articles for article (PubMed ID: 34207807)
1. Soft-Sensor for Class Prediction of the Percentage of Pentanes in Butane at a Debutanizer Column.
Niño-Adan I; Landa-Torres I; Manjarres D; Portillo E; Orbe L
Sensors (Basel); 2021 Jun; 21(12):. PubMed ID: 34207807
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. Hierarchical automated machine learning (AutoML) for advanced unconventional reservoir characterization.
Mubarak Y; Koeshidayatullah A
Sci Rep; 2023 Aug; 13(1):13812. PubMed ID: 37620388
[TBL] [Abstract][Full Text] [Related]
4. Automated machine learning: Review of the state-of-the-art and opportunities for healthcare.
Waring J; Lindvall C; Umeton R
Artif Intell Med; 2020 Apr; 104():101822. PubMed ID: 32499001
[TBL] [Abstract][Full Text] [Related]
5. AutoML-ID: automated machine learning model for intrusion detection using wireless sensor network.
Singh A; Amutha J; Nagar J; Sharma S; Lee CC
Sci Rep; 2022 May; 12(1):9074. PubMed ID: 35641584
[TBL] [Abstract][Full Text] [Related]
6. Automated machine learning in nanotoxicity assessment: A comparative study of predictive model performance.
Xiao X; Trinh TX; Gerelkhuu Z; Ha E; Yoon TH
Comput Struct Biotechnol J; 2024 Dec; 25():9-19. PubMed ID: 38414794
[TBL] [Abstract][Full Text] [Related]
7. Pharm-AutoML: An open-source, end-to-end automated machine learning package for clinical outcome prediction.
Liu G; Lu D; Lu J
CPT Pharmacometrics Syst Pharmacol; 2021 May; 10(5):478-488. PubMed ID: 33793093
[TBL] [Abstract][Full Text] [Related]
8. Machine Learning Models for Slope Stability Classification of Circular Mode Failure: An Updated Database and Automated Machine Learning (AutoML) Approach.
Ma J; Jiang S; Liu Z; Ren Z; Lei D; Tan C; Guo H
Sensors (Basel); 2022 Nov; 22(23):. PubMed ID: 36501865
[TBL] [Abstract][Full Text] [Related]
9. Algorithm Recommendation and Performance Prediction Using Meta-Learning.
Palumbo G; Carneiro D; Guimares M; Alves V; Novais P
Int J Neural Syst; 2023 Mar; 33(3):2350011. PubMed ID: 36722692
[TBL] [Abstract][Full Text] [Related]
10. A Bibliometric Analysis and Benchmark of Machine Learning and AutoML in Crash Severity Prediction: The Case Study of Three Colombian Cities.
Angarita-Zapata JS; Maestre-Gongora G; Calderín JF
Sensors (Basel); 2021 Dec; 21(24):. PubMed ID: 34960494
[TBL] [Abstract][Full Text] [Related]
11. BioAutoML: automated feature engineering and metalearning to predict noncoding RNAs in bacteria.
Bonidia RP; Santos APA; de Almeida BLS; Stadler PF; da Rocha UN; Sanches DS; de Carvalho ACPLF
Brief Bioinform; 2022 Jul; 23(4):. PubMed ID: 35753697
[TBL] [Abstract][Full Text] [Related]
12. Searching for the urine osmolality surrogate: an automated machine learning approach.
Topcu Dİ; Bayraktar N
Clin Chem Lab Med; 2022 Nov; 60(12):1911-1920. PubMed ID: 35778953
[TBL] [Abstract][Full Text] [Related]
13. Automating water quality analysis using ML and auto ML techniques.
Venkata Vara Prasad D; Senthil Kumar P; Venkataramana LY; Prasannamedha G; Harshana S; Jahnavi Srividya S; Harrinei K; Indraganti S
Environ Res; 2021 Nov; 202():111720. PubMed ID: 34297938
[TBL] [Abstract][Full Text] [Related]
14. Biomedical image classification made easier thanks to transfer and semi-supervised learning.
Inés A; Domínguez C; Heras J; Mata E; Pascual V
Comput Methods Programs Biomed; 2021 Jan; 198():105782. PubMed ID: 33065493
[TBL] [Abstract][Full Text] [Related]
15. AutoDC: an automatic machine learning framework for disease classification.
Bai Y; Li Y; Shen Y; Yang M; Zhang W; Cui B
Bioinformatics; 2022 Jun; 38(13):3415-3421. PubMed ID: 35583303
[TBL] [Abstract][Full Text] [Related]
16. Comparisons of automated machine learning (AutoML) in predicting whistleblowing of academic dishonesty with demographic and theory of planned behavior.
Rahman RA; Masrom S; Mohamad M; Sari EN; Saragih F; Rahman ASA
MethodsX; 2023 Dec; 11():102364. PubMed ID: 37744883
[TBL] [Abstract][Full Text] [Related]
17. Sensor Failure Tolerable Machine Learning-Based Food Quality Prediction Model.
Kaya A; Keçeli AS; Catal C; Tekinerdogan B
Sensors (Basel); 2020 Jun; 20(11):. PubMed ID: 32503198
[TBL] [Abstract][Full Text] [Related]
18. A Deep Supervised Learning Framework for Data-Driven Soft Sensor Modeling of Industrial Processes.
Yuan X; Gu Y; Wang Y; Yang C; Gui W
IEEE Trans Neural Netw Learn Syst; 2020 Nov; 31(11):4737-4746. PubMed ID: 31880568
[TBL] [Abstract][Full Text] [Related]
19. Predicting cervical cancer risk probabilities using advanced H20 AutoML and local interpretable model-agnostic explanation techniques.
Prusty S; Patnaik S; Dash SK; Prusty SGP; Rautaray J; Sahoo G
PeerJ Comput Sci; 2024; 10():e1916. PubMed ID: 38855252
[TBL] [Abstract][Full Text] [Related]
20. Variational Progressive-Transfer Network for Soft Sensing of Multirate Industrial Processes.
Chai Z; Zhao C; Huang B
IEEE Trans Cybern; 2022 Dec; 52(12):12882-12892. PubMed ID: 34357875
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
