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XGBFEMF: An XGBoost-Based Framework for Essential Protein Prediction
XGBFEMF: An XGBoost-Based Framework for Essential Protein Prediction
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XGBFEMF: An XGBoost-Based Framework for Essential Protein Prediction

Zhong, Jiancheng ; Sun, Yusui ; Peng, Wei ; Xie, Minzhu ; Yang, Jiahong ; Tang, Xiwei

IEEE transactions on nanobioscience, 2018-07, Vol.17 (3), p.243-250

United States: IEEE

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Deep Patient Similarity Learning for Personalized Healthcare
Deep Patient Similarity Learning for Personalized Healthcare
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Deep Patient Similarity Learning for Personalized Healthcare

Suo, Qiuling ; Ma, Fenglong ; Yuan, Ye ; Huai, Mengdi ; Zhong, Weida ; Gao, Jing ; Zhang, Aidong

IEEE transactions on nanobioscience, 2018-07, Vol.17 (3), p.219-227

United States: IEEE

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Predictive Models on the Rise, But Do They Work for Health Care?
Predictive Models on the Rise, But Do They Work for Health Care?
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Predictive Models on the Rise, But Do They Work for Health Care?

Mertz, Leslie

IEEE pulse, 2020-11, Vol.11 (6), p.10-13

United States: IEEE

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4
AI Tools Poised to Improve Patient Health Care
AI Tools Poised to Improve Patient Health Care
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AI Tools Poised to Improve Patient Health Care

Mertz, Leslie

IEEE pulse, 2022-03, Vol.13 (2), p.2-6

United States: IEEE

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5
Predicting plant miRNA-lncRNA interactions via a deep learning method
Predicting plant miRNA-lncRNA interactions via a deep learning method
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Predicting plant miRNA-lncRNA interactions via a deep learning method

Tang, Xiwei ; Ji, Lu

IEEE transactions on nanobioscience, 2023-10, Vol.PP (4), p.1-1

United States: IEEE

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6
Protein Function Prediction with Functional and Topological Knowledge of Gene Ontology
Protein Function Prediction with Functional and Topological Knowledge of Gene Ontology
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Protein Function Prediction with Functional and Topological Knowledge of Gene Ontology

Zhao, Yingwen ; Yang, Zhihao ; Hong, Yongkai ; Yang, Yumeng ; Wang, Lei ; Zhang, Yin ; Lin, Hongfei ; Wang, Jian

IEEE transactions on nanobioscience, 2023-10, Vol.PP (4), p.1-1

United States: IEEE

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Prediction of Cancer Metastasis using Correlations between miRNAs and Competing Endogenous RNAs
Prediction of Cancer Metastasis using Correlations between miRNAs and Competing Endogenous RNAs
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Prediction of Cancer Metastasis using Correlations between miRNAs and Competing Endogenous RNAs

Cho, Myeonghun ; Lee, Seokwoo ; Park, Byungkyu ; Han, Kyungsook

IEEE transactions on nanobioscience, 2023-10, Vol.PP (4), p.1-1

United States: IEEE

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8
A Deep Learning Regression Model for Photonic Crystal Fiber Sensor with XAI Feature Selection and Analysis
A Deep Learning Regression Model for Photonic Crystal Fiber Sensor with XAI Feature Selection and Analysis
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A Deep Learning Regression Model for Photonic Crystal Fiber Sensor with XAI Feature Selection and Analysis

Vijayan, Mochitha ; Sridhar, S.S. ; Vijayalakshmi, Dhinakaran

IEEE transactions on nanobioscience, 2023-07, Vol.22 (3), p.1-1

United States: IEEE

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9
Individualized seizure cluster prediction using machine learning and chronic ambulatory intracranial EEG
Individualized seizure cluster prediction using machine learning and chronic ambulatory intracranial EEG
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Individualized seizure cluster prediction using machine learning and chronic ambulatory intracranial EEG

Saboo, Krishnakant V. ; Cao, Yurui ; Kremen, Vaclav ; Sladky, Vladimir ; Gregg, Nicholas M. ; Arnold, Paul M. ; Karoly, Philippa J. ; Freestone, Dean R. ; Cook, Mark J. ; Worrell, Gregory A. ; Iyer, Ravishankar K.

IEEE transactions on nanobioscience, 2023-10, Vol.22 (4), p.1-1

United States: IEEE

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10
Unusual Observations in the Wear-Out of High-Purity Aluminum Wire Bonds Under Extended Range Passive Thermal Cycling
Unusual Observations in the Wear-Out of High-Purity Aluminum Wire Bonds Under Extended Range Passive Thermal Cycling
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Unusual Observations in the Wear-Out of High-Purity Aluminum Wire Bonds Under Extended Range Passive Thermal Cycling

Agyakwa, Pearl A ; Corfield, Martin R ; Jian Feng Li ; Wei-Sun Loh ; Liotti, Enzo ; Hogg, Simon C ; Johnson, C Mark

IEEE transactions on device and materials reliability, 2010-06, Vol.10 (2), p.254-262 [Periódico revisado por pares]

New York: IEEE

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