Machine Learning in Transportation by Ali Tizghadam, Hamzeh Khazaei, Mohammad H. Y. Moghaddam, Yasser Hassan

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Primer on Machine Learning in Electrophysiology by Shane E Loeffler, Natalia Trayanova

“…Machine learning applications are expected to change contemporary medicine as they are brought into mainstream clinical practice. …”
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Data normalization in machine learning by V. V. Starovoitov, Yu. I. Golub

“…In machine learning, the input data is often given in different dimensions. …”
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Machine Learning in Medical Imaging by Kenji Suzuki, Pingkun Yan, Fei Wang, Dinggang Shen

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Machine Learning Potential for Serpentines by Hongjin Wang, Chenxing Luo, Renata M. Wentzcovitch

“…Journal of Geophysical Research: Machine Learning and Computation…”
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Machine learning for drug science by Walter F. de Azevedo Jr.

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Is Machine Learning Real Learning? by Zdenko Kodelja

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Business Valuation with Machine learning by P. S. Koklev

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The machine learning in the prediction of elections by M.S.C. José A. León-Borges, M.A. Roger-Ismael-Noh-Balam, Lic. Lino Rangel Gómez, Br. Michael Philip Strand

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Machine learning in electroconvulsive therapy by Robert Lundin, Moloud Abdar, Abbas Khosravi, Colleen Loo, Michael Berk

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Machine learning electroweakino production by Rafał Masełek, Mihoko M. Nojiri, Kazuki Sakurai

“…In this study, we explore Machine Learning (ML) methods for efficient signal/background discrimination. …”
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Machine Learning in the National Economy by Azamjon A. Usmonov

Subjects: “…machine learning…”
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Machine Learning and Visual Computing by Lei Zhang, Yu Cao, Fei Yang, Qiushi Zhao

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Searching for ribbons with machine learning by Sergei Gukov, James Halverson, Ciprian Manolescu, Fabian Ruehle

“…Machine Learning: Science and Technology…”
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AN ADVANCED MACHINE LEARNING (ML) ARCHITECTURE FOR HEART DISEASE DETECTION, PREDICTION AND CLASSIFICATION USING MACHINE LEARNING by Muhammad Anas, Muhammad Atif Imtiaz, Saad Khan, Arshad Ali, Noor Fatima Naghman, Hamayun Khan, Sami Albouq

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Comparing Scientific Machine Learning With Population Pharmacokinetic and Classical Machine Learning Approaches for Prediction of Drug Concentrations by Diego Valderrama, Olga Teplytska, Luca Marie Koltermann, Elena Trunz, Eduard Schmulenson, Achim Fritsch, Ulrich Jaehde, Holger Fröhlich

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Machine learning in Alzheimer’s disease genetics by Matthew Bracher-Smith, Federico Melograna, Brittany Ulm, Céline Bellenguez, Benjamin Grenier-Boley, Diane Duroux, Alejo J. Nevado, Peter Holmans, Betty M. Tijms, Marc Hulsman, Itziar de Rojas, Rafael Campos-Martin, Sven van der Lee, Atahualpa Castillo, Fahri Küçükali, Oliver Peters, Anja Schneider, Martin Dichgans, Dan Rujescu, Norbert Scherbaum, Jürgen Deckert, Steffi Riedel-Heller, Lucrezia Hausner, Laura Molina-Porcel, Emrah Düzel, Timo Grimmer, Jens Wiltfang, Stefanie Heilmann-Heimbach, Susanne Moebus, Thomas Tegos, Nikolaos Scarmeas, Oriol Dols-Icardo, Fermin Moreno, Jordi Pérez-Tur, María J. Bullido, Pau Pastor, Raquel Sánchez-Valle, Victoria Álvarez, Mercè Boada, Pablo García-González, Raquel Puerta, Pablo Mir, Luis M. Real, Gerard Piñol-Ripoll, Jose María García-Alberca, Eloy Rodriguez-Rodriguez, Hilkka Soininen, Sami Heikkinen, Alexandre de Mendonça, Shima Mehrabian, Latchezar Traykov, Jakub Hort, Martin Vyhnalek, Nicolai Sandau, Jesper Qvist Thomassen, Yolande A. L. Pijnenburg, Henne Holstege, John van Swieten, Inez Ramakers, Frans Verhey, Philip Scheltens, Caroline Graff, Goran Papenberg, Vilmantas Giedraitis, Julie Williams, Philippe Amouyel, Anne Boland, Jean-François Deleuze, Gael Nicolas, Carole Dufouil, Florence Pasquier, Olivier Hanon, Stéphanie Debette, Edna Grünblatt, Julius Popp, Roberta Ghidoni, Daniela Galimberti, Beatrice Arosio, Patrizia Mecocci, Vincenzo Solfrizzi, Lucilla Parnetti, Alessio Squassina, Lucio Tremolizzo, Barbara Borroni, Michael Wagner, Benedetta Nacmias, Marco Spallazzi, Davide Seripa, Innocenzo Rainero, Antonio Daniele, Fabrizio Piras, Carlo Masullo, Giacomina Rossi, Frank Jessen, Patrick Kehoe, Tsolaki Magda, Pascual Sánchez-Juan, Kristel Sleegers, Martin Ingelsson, Mikko Hiltunen, Rebecca Sims, Wiesje van der Flier, Ole A. Andreassen, Agustín Ruiz, Alfredo Ramirez, EADB, Ruth Frikke-Schmidt, Najaf Amin, Gennady Roshchupkin, Jean-Charles Lambert, Kristel Van Steen, Cornelia van Duijn, Valentina Escott-Price

“…Here we applied machine learning (ML) to genome-wide data from 41,686 individuals in the largest European consortium on Alzheimer’s disease (AD) to investigate the effectiveness of various ML algorithms in replicating known findings, discovering novel loci, and predicting individuals at risk. …”
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In-depth Analysis on Machine Learning Approaches by Abdulhady A. Abdullah, Nergz S. Mohammed, Maryam Khanzadi, Safar M. Asaad, Zrar Kh. Abdul, Halgurd S. Maghdid

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