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1-Year Mortality Prediction through Artificial Intelligence Using Hemodynamic Trace Analysis among Patients with ST Elevation Myocardial Infarction
1-Year Mortality Prediction through Artificial Intelligence Using Hemodynamic Trace Analysis among Patients with ST Elevation Myocardial Infarction
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1-Year Mortality Prediction through Artificial Intelligence Using Hemodynamic Trace Analysis among Patients with ST Elevation Myocardial Infarction

Razavi, Seyed Reza ; Szun, Tyler ; Zaremba, Alexander C ; Shah, Ashish H ; Moussavi, Zahra

Medicina (Kaunas, Lithuania), 2024-04, Vol.60 (4), p.558 [Periódico revisado por pares]

Switzerland: MDPI AG

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16S classifier: a tool for fast and accurate taxonomic classification of 16S rRNA hypervariable regions in metagenomic datasets
16S classifier: a tool for fast and accurate taxonomic classification of 16S rRNA hypervariable regions in metagenomic datasets
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16S classifier: a tool for fast and accurate taxonomic classification of 16S rRNA hypervariable regions in metagenomic datasets

Chaudhary, Nikhil ; Sharma, Ashok K ; Agarwal, Piyush ; Gupta, Ankit ; Sharma, Vineet K Dalby, Andrew R.

PloS one, 2015-02, Vol.10 (2), p.e0116106-e0116106 [Periódico revisado por pares]

United States: Public Library of Science

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3
16S rRNA sequence embeddings: Meaningful numeric feature representations of nucleotide sequences that are convenient for downstream analyses
16S rRNA sequence embeddings: Meaningful numeric feature representations of nucleotide sequences that are convenient for downstream analyses
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16S rRNA sequence embeddings: Meaningful numeric feature representations of nucleotide sequences that are convenient for downstream analyses

Woloszynek, Stephen ; Zhao, Zhengqiao ; Chen, Jian ; Rosen, Gail L Langille, Morgan

PLoS computational biology, 2019-02, Vol.15 (2), p.e1006721-e1006721 [Periódico revisado por pares]

United States: Public Library of Science

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4
18F-FET PET radiomics-based survival prediction in glioblastoma patients receiving radio(chemo)therapy
18F-FET PET radiomics-based survival prediction in glioblastoma patients receiving radio(chemo)therapy
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18F-FET PET radiomics-based survival prediction in glioblastoma patients receiving radio(chemo)therapy

Wiltgen, Tun ; Fleischmann, Daniel F. ; Kaiser, Lena ; Holzgreve, Adrien ; Corradini, Stefanie ; Landry, Guillaume ; Ingrisch, Michael ; Popp, Ilinca ; Grosu, Anca L. ; Unterrainer, Marcus ; Bartenstein, Peter ; Parodi, Katia ; Belka, Claus ; Albert, Nathalie ; Niyazi, Maximilian ; Riboldi, Marco

Radiation oncology (London, England), 2022-12, Vol.17 (1), p.1-11, Article 198 [Periódico revisado por pares]

London: BioMed Central

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5
1D-CNN: Classification of normal delivery and cesarean section types using cardiotocography time-series signals
1D-CNN: Classification of normal delivery and cesarean section types using cardiotocography time-series signals
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1D-CNN: Classification of normal delivery and cesarean section types using cardiotocography time-series signals

Kurtadikar, Vidya Sujit ; Pande, Himangi Milind

Journal of intelligent systems, 2024-05, Vol.33 (1), p.13-24 [Periódico revisado por pares]

Berlin: De Gruyter

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6
2-D chemical structure image-based in silico model to predict agonist activity for androgen receptor
2-D chemical structure image-based in silico model to predict agonist activity for androgen receptor
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2-D chemical structure image-based in silico model to predict agonist activity for androgen receptor

Yu, Myeong-Sang ; Lee, Jingyu ; Lee, Yongmin ; Na, Dokyun

BMC bioinformatics, 2020-10, Vol.21 (Suppl 5), p.1-245, Article 245 [Periódico revisado por pares]

London: BioMed Central Ltd

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7
20 cm resolution mapping of tundra vegetation communities provides an ecological baseline for important research areas in a changing Arctic environment
20 cm resolution mapping of tundra vegetation communities provides an ecological baseline for important research areas in a changing Arctic environment
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20 cm resolution mapping of tundra vegetation communities provides an ecological baseline for important research areas in a changing Arctic environment

Greaves, Heather E ; Eitel, Jan U H ; Vierling, Lee A ; Boelman, Natalie T ; Griffin, Kevin L ; Magney, Troy S ; Prager, Case M

Environmental Research Communications, 2019-11, Vol.1 (10), p.105004 [Periódico revisado por pares]

Bristol: IOP Publishing

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8
2D Semantic Segmentation: Recent Developments and Future Directions
2D Semantic Segmentation: Recent Developments and Future Directions
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2D Semantic Segmentation: Recent Developments and Future Directions

Guo, Yu ; Nie, Guigen ; Gao, Wenliang ; Liao, Mi

Future internet, 2023-06, Vol.15 (6), p.205 [Periódico revisado por pares]

Basel: MDPI AG

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9
3-D Channel and Spatial Attention Based Multiscale Spatial-Spectral Residual Network for Hyperspectral Image Classification
3-D Channel and Spatial Attention Based Multiscale Spatial-Spectral Residual Network for Hyperspectral Image Classification
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3-D Channel and Spatial Attention Based Multiscale Spatial-Spectral Residual Network for Hyperspectral Image Classification

Lu, Zhenyu ; Xu, Bin ; Sun, Le ; Zhan, Tianming ; Tang, Songze

IEEE journal of selected topics in applied earth observations and remote sensing, 2020, Vol.13, p.4311-4324 [Periódico revisado por pares]

Piscataway: IEEE

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10
3-D Hybrid CNN Combined With 3-D Generative Adversarial Network for Wetland Classification With Limited Training Data
3-D Hybrid CNN Combined With 3-D Generative Adversarial Network for Wetland Classification With Limited Training Data
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3-D Hybrid CNN Combined With 3-D Generative Adversarial Network for Wetland Classification With Limited Training Data

Jamali, Ali ; Mahdianpari, Masoud ; Mohammadimanesh, Fariba ; Brisco, Brian ; Salehi, Bahram

IEEE journal of selected topics in applied earth observations and remote sensing, 2022, Vol.15, p.8095-8108 [Periódico revisado por pares]

Piscataway: IEEE

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