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Machine learning

Machine learning provides evidence that stroke risk is not linear: The non-linear Framingham stroke risk score

Agni Orfanoudaki, Emma Chesley, Christian Cadisch, Barry Stein, Amre Nouh, Mark J. Alberts, Dimitris Bertsimas

published 21 May 2020

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Artificial intelligence may offer insight into factors determining individual TSH level

Prasanna Santhanam, Tanmay Nath, Faiz Khan Mohammad, Rexford S. Ahima

published 20 May 2020

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Laboratory-based and free-living algorithms for energy expenditure estimation in preschool children: A free-living evaluation

Matthew N. Ahmadi, Alok Chowdhury, Toby Pavey, Stewart G. Trost

published 20 May 2020

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Osteoporotic hip fracture prediction from risk factors available in administrative claims data – A machine learning approach

Alexander Engels, Katrin C. Reber, Ivonne Lindlbauer, Kilian Rapp, Gisela Büchele, Jochen Klenk, Andreas Meid, Clemens Becker, Hans-Helmut König

published 19 May 2020

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ToyArchitecture: Unsupervised learning of interpretable models of the environment

Jaroslav Vítků, Petr Dluhoš, Joseph Davidson, Matěj Nikl, Simon Andersson, Přemysl Paška, Jan Šinkora, Petr Hlubuček, Martin Stránský, Martin Hyben, Martin Poliak, Jan Feyereisl, Marek Rosa

published 18 May 2020

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Neural networks for open and closed Literature-based Discovery

Gamal Crichton, Simon Baker, Yufan Guo, Anna Korhonen

published 15 May 2020

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OtoMatch: Content-based eardrum image retrieval using deep learning

Seda Camalan, Muhammad Khalid Khan Niazi, Aaron C. Moberly, Theodoros Teknos, Garth Essig, Charles Elmaraghy, Nazhat Taj-Schaal, Metin N. Gurcan

published 15 May 2020

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Innovative machine learning approach and evaluation campaign for predicting the subjective feeling of work-life balance among employees

Aleksandra Pawlicka, Marek Pawlicki, Renata Tomaszewska, Michał Choraś, Ryszard Gerlach

published 15 May 2020

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Deep neural model with self-training for scientific keyphrase extraction

Xun Zhu, Chen Lyu, Donghong Ji, Han Liao, Fei Li

published 15 May 2020

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Prediction of hypertension, hyperglycemia and dyslipidemia from retinal fundus photographs via deep learning: A cross-sectional study of chronic diseases in central China

Li Zhang, Mengya Yuan, Zhen An, Xiangmei Zhao, Hui Wu, Haibin Li, Ya Wang, Beibei Sun, Huijun Li, Shibin Ding, Xiang Zeng, Ling Chao, Pan Li, Weidong Wu

published 14 May 2020

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Deep learning assisted detection of glaucomatous optic neuropathy and potential designs for a generalizable model

Yu-Chieh Ko, Shih-Yu Wey, Wei-Ta Chen, Yu-Fan Chang, Mei-Ju Chen, Shih-Hwa Chiou, Catherine Jui-Ling Liu, Chen-Yi Lee

published 14 May 2020

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Disentangling sequential from hierarchical learning in Artificial Grammar Learning: Evidence from a modified Simon Task

Maria Vender, Diego Gabriel Krivochen, Arianna Compostella, Beth Phillips, Denis Delfitto, Douglas Saddy

published 14 May 2020

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Improvement of electrocardiographic diagnostic accuracy of left ventricular hypertrophy using a Machine Learning approach

Fernando De la Garza-Salazar, Maria Elena Romero-Ibarguengoitia, Elias Abraham Rodriguez-Diaz, Jose Ramón Azpiri-Lopez, Arnulfo González-Cantu

published 13 May 2020

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