Nyarko EK - Search Results

1

Advancements in Computer-Aided Diagnosis of Celiac Disease: A Systematic Review.

Hartmann Tolić I, Habijan M, Galić I, Nyarko EK. Hartmann Tolić I, et al. Among authors: nyarko ek. Biomimetics (Basel). 2024 Aug 14;9(8):493. doi: 10.3390/biomimetics9080493. Biomimetics (Basel). 2024. PMID: 39194472 Free PMC article. Review.

2

Automatic Robot-Driven 3D Reconstruction System for Chronic Wounds.

Filko D, Marijanović D, Nyarko EK. Filko D, et al. Among authors: nyarko ek. Sensors (Basel). 2021 Dec 12;21(24):8308. doi: 10.3390/s21248308. Sensors (Basel). 2021. PMID: 34960402 Free PMC article.

3

2D/3D Wound Segmentation and Measurement Based on a Robot-Driven Reconstruction System.

Filko D, Nyarko EK. Filko D, et al. Among authors: nyarko ek. Sensors (Basel). 2023 Mar 21;23(6):3298. doi: 10.3390/s23063298. Sensors (Basel). 2023. PMID: 36992009 Free PMC article.

4

Modelling the Influence of Waste Rubber on Compressive Strength of Concrete by Artificial Neural Networks.

Hadzima-Nyarko M, Nyarko EK, Ademović N, Miličević I, Kalman Šipoš T. Hadzima-Nyarko M, et al. Among authors: nyarko ek. Materials (Basel). 2019 Feb 13;12(4):561. doi: 10.3390/ma12040561. Materials (Basel). 2019. PMID: 30781883 Free PMC article.

5

Modeling of Compressive Strength of Self-Compacting Rubberized Concrete Using Machine Learning.

Kovačević M, Lozančić S, Nyarko EK, Hadzima-Nyarko M. Kovačević M, et al. Among authors: nyarko ek. Materials (Basel). 2021 Aug 3;14(15):4346. doi: 10.3390/ma14154346. Materials (Basel). 2021. PMID: 34361540 Free PMC article.

6

Application of Artificial Intelligence Methods for Predicting the Compressive Strength of Self-Compacting Concrete with Class F Fly Ash.

Kovačević M, Lozančić S, Nyarko EK, Hadzima-Nyarko M. Kovačević M, et al. Among authors: nyarko ek. Materials (Basel). 2022 Jun 13;15(12):4191. doi: 10.3390/ma15124191. Materials (Basel). 2022. PMID: 35744253 Free PMC article.

7

Application of Machine Learning in Modeling the Relationship between Catchment Attributes and Instream Water Quality in Data-Scarce Regions.

Kovačević M, Jabbarian Amiri B, Lozančić S, Hadzima-Nyarko M, Radu D, Nyarko EK. Kovačević M, et al. Among authors: nyarko ek. Toxics. 2023 Dec 7;11(12):996. doi: 10.3390/toxics11120996. Toxics. 2023. PMID: 38133397 Free PMC article.

8

Modelling daily water temperature from air temperature for the Missouri River.

Zhu S, Nyarko EK, Hadzima-Nyarko M. Zhu S, et al. Among authors: nyarko ek. PeerJ. 2018 Jun 7;6:e4894. doi: 10.7717/peerj.4894. eCollection 2018. PeerJ. 2018. PMID: 29892503 Free PMC article.

9

Assessing the performance of a suite of machine learning models for daily river water temperature prediction.

Zhu S, Nyarko EK, Hadzima-Nyarko M, Heddam S, Wu S. Zhu S, et al. Among authors: nyarko ek. PeerJ. 2019 Jun 4;7:e7065. doi: 10.7717/peerj.7065. eCollection 2019. PeerJ. 2019. PMID: 31198649 Free PMC article.

10

Modeling daily water temperature for rivers: comparison between adaptive neuro-fuzzy inference systems and artificial neural networks models.

Zhu S, Heddam S, Nyarko EK, Hadzima-Nyarko M, Piccolroaz S, Wu S. Zhu S, et al. Among authors: nyarko ek. Environ Sci Pollut Res Int. 2019 Jan;26(1):402-420. doi: 10.1007/s11356-018-3650-2. Epub 2018 Nov 7. Environ Sci Pollut Res Int. 2019. PMID: 30406582

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