Comprehensive Machine Learning Analysis on the Phenotypes of COVID-19 Patients Using Transcriptome Data.
- Published in:
- Arab Gulf Journal of Scientific Research, 2021, v. 39, p. 79
- By:
- Publication type:
- Article
Works by Jeyananthan, Pratheeba
Results: 11
1
2
Quantifying the impact of chemical composition on pervious concrete strength: a comparative analysis using full quadratic model and artificial neural network.
- Published in:
- International Journal of Pavement Engineering, 2024, v. 25, n. 1, p. 1, doi. 10.1080/10298436.2024.2424381
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- Publication type:
- Article
3
Soft computing to predict the porosity and permeability of pervious concrete based on mix design and ultrasonic pulse velocity.
- Published in:
- International Journal of Pavement Engineering, 2024, v. 25, n. 1, p. 1, doi. 10.1080/10298436.2024.2337916
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- Publication type:
- Article
4
Prediction of compressive strength of fly ash blended pervious concrete: a machine learning approach.
- Published in:
- International Journal of Pavement Engineering, 2023, v. 24, n. 2, p. 1, doi. 10.1080/10298436.2023.2287146
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- Publication type:
- Article
5
Response surface regression and machine learning models to predict the porosity and compressive strength of pervious concrete based on mix design parameters.
- Published in:
- Road Materials & Pavement Design, 2025, v. 26, n. 3, p. 618, doi. 10.1080/14680629.2024.2374885
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- Publication type:
- Article
6
Prediction of moisture content of cement-stabilized earth blocks using soil characteristics, cement content, and ultrasonic pulse velocity.
- Published in:
- Journal of Engineering & Applied Science, 2024, v. 71, n. 1, p. 1, doi. 10.1186/s44147-024-00527-2
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- Publication type:
- Article
7
Soft computing techniques to predict the compressive strength of groundnut shell ash-blended concrete.
- Published in:
- Journal of Engineering & Applied Science, 2023, v. 70, n. 1, p. 1, doi. 10.1186/s44147-023-00302-9
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- Publication type:
- Article
8
Characterization of the shape of aggregates using image analysis and machine learning classification tools.
- Published in:
- Geomechanics & Geoengineering, 2024, v. 19, n. 4, p. 421, doi. 10.1080/17486025.2023.2288655
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- Publication type:
- Article
9
Predicting compressive strength of quarry waste-based geopolymer mortar using machine learning algorithms incorporating mix design and ultrasonic pulse velocity.
- Published in:
- Nondestructive Testing & Evaluation, 2024, v. 39, n. 8, p. 2486, doi. 10.1080/10589759.2024.2304257
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- Publication type:
- Article
10
Predicting compressive strength of cement-stabilized earth blocks using machine learning models incorporating cement content, ultrasonic pulse velocity, and electrical resistivity.
- Published in:
- Nondestructive Testing & Evaluation, 2024, v. 39, n. 5, p. 1045, doi. 10.1080/10589759.2023.2240940
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- Publication type:
- Article
11
On integrative analysis of multi-level gene expression data in Kidney cancer subgrouping.
- Published in:
- Urologia Journal, 2025, v. 92, n. 2, p. 194, doi. 10.1177/03915603241304604
- By:
- Publication type:
- Article