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Communication

Artificially Intelligent Nanoarray for the Detection of Preeclampsia under Real‐World Clinical Conditions

Morad K. Nakhleh

Department of Chemical Engineering and the Russell Berrie Nanotechnology Institute, Technion ‐ Israel Institute of TechnologyHaifa, Israel

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Shira Baram

Department of Obstetrics and Gynecology, Emek Medical CenterAfula, Israel

Rappaport Family Faculty of Medicine, Technion—Israel Institute of TechnologyHaifa, Israel

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Raneen Jeries

Department of Chemical Engineering and the Russell Berrie Nanotechnology Institute, Technion ‐ Israel Institute of TechnologyHaifa, Israel

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Raed Salim

Department of Obstetrics and Gynecology, Emek Medical CenterAfula, Israel

Rappaport Family Faculty of Medicine, Technion—Israel Institute of TechnologyHaifa, Israel

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Hossam Haick

Corresponding Author

E-mail address:hhossam@technion.ac.il

Department of Chemical Engineering and the Russell Berrie Nanotechnology Institute, Technion ‐ Israel Institute of TechnologyHaifa, Israel

E‐mail: E-mail address:hhossam@technion.ac.il
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Marwan Hakim

Department of Obstetrics and Gynecology, Nazareth Hospital EMMSNazareth, Israel

Faculty of Medicine in the Galilee, Bar‐Ilan UniversityRamat‐Gan, Israel

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First published: 30 September 2016
Cited by: 4

Abstract

Artificially intelligent nanoarray based on molecularly‐modified gold nanoparticles is tailored for the detection of preeclampsia by noninvasive breathprint analysis. The diagnostic power of the nanoarray under actual clinical conditions shows discrimination between preeclampsia and nonpreeclamptic pregnancy with an 84% accuracy, and between preeclampsia and nonpregnant women with 87% accuracy.

Number of times cited: 4

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