D
Dmitriy Fradkin
Researcher at Princeton University
Publications - 45
Citations - 1917
Dmitriy Fradkin is an academic researcher from Princeton University. The author has contributed to research in topics: Cluster analysis & Support vector machine. The author has an hindex of 17, co-authored 44 publications receiving 1668 citations. Previous affiliations of Dmitriy Fradkin include Rutgers University & Eindhoven University of Technology.
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Journal ArticleDOI
Atlas of the clinical genetics of human dilated cardiomyopathy
Jan Haas,Karen S. Frese,Barbara Peil,Wanda Kloos,Andreas Keller,Rouven Nietsch,Zhu Feng,Sabine Müller,Elham Kayvanpour,Britta Vogel,Farbod Sedaghat-Hamedani,Wei Keat Lim,Xiaohong Zhao,Dmitriy Fradkin,Doreen Köhler,Simon Fischer,Jennifer Franke,Sabine Marquart,Ioana Barb,Daniel Tian Li,Ali Amr,Philipp Ehlermann,Derliz Mereles,Tanja Weis,Sarah Hassel,Andreas Kremer,Vanessa King,Emil Wirsz,Emil Wirsz,Richard Isnard,Michel Komajda,Alessandra Serio,Maurizia Grasso,Petros Syrris,Eleanor Wicks,Vincent Plagnol,Luis R. Lopes,Tenna Gadgaard,Hans Eiskjær,Mads E. Jørgensen,Diego García-Giustiniani,Martin Ortiz-Genga,María G. Crespo-Leiro,Rondal H Lekanne Dit Deprez,Imke Christiaans,Ingrid A.W. van Rijsingen,Arthur A.M. Wilde,Anders Waldenström,Martino Bolognesi,Riccardo Bellazzi,Stellan Mörner,Justo Lorenzo Bermejo,Lorenzo Monserrat,Eric Villard,Jens Mogensen,Yigal M. Pinto,Philippe Charron,Perry M. Elliott,Eloisa Arbustini,Hugo A. Katus,Benjamin Meder +60 more
TL;DR: This is to the authors' knowledge, the first study that comprehensively investigated the genetics of DCM in a large-scale cohort and across a broad gene panel of the known DCM genes and underline the high analytical quality and feasibility of Next-Generation Sequencing in clinical genetic diagnostics.
Proceedings ArticleDOI
Experiments with random projections for machine learning
Dmitriy Fradkin,David Madigan +1 more
TL;DR: It is found that the random projection approach predictively underperforms PCA, but its computational advantages may make it attractive for certain applications.
Proceedings ArticleDOI
Log-based predictive maintenance
TL;DR: Predictive maintenance techniques help determine the condition of in-service equipment in order to predict when and what repairs should be performed to prevent unexpected equipment failures.
Proceedings ArticleDOI
Mining recent temporal patterns for event detection in multivariate time series data
TL;DR: This work introduces the recent temporal pattern mining framework for finding predictive patterns for monitoring and event detection problems in complex multivariate time series data and applies it to health care data of 13,558 diabetic patients.
Journal ArticleDOI
Mining Compressing Sequential Patterns
TL;DR: This article proposes GoKrimp, an algorithm that directly mines compressing patterns by greedily extending a pattern until no additional compression benefit of adding the extension into the dictionary, and proposes a dependency test which only chooses related events for extending a given pattern.