Risultati della ricerca

Exploring Word Embedding for Drug Name Recognition di Isabel Segura-Bedmar, Víctor Suárez-Paniagua, Paloma Martı́nez

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Word2Vec inversion and traditional text classifiers for phenotyping lupus di Clayton A. Turner, A. Jacobs, Cassios K. Marques, Jim C. Oates, Diane L. Kamen, Paul E. Anderson, Jihad S. Obeid

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Drug drug interaction extraction from biomedical literature using syntax convolutional neural network di Zhehuan Zhao, Zhihao Yang, Ling Luo, Hongfei Lin, Jian Wang

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Visually Grounded and Textual Semantic Models Differentially Decode Brain Activity Associated with Concrete and Abstract Nouns di Andrew Anderson, Douwe Kiela, Stephen Clark, Massimo Poesio

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Clinical use of semantic space models in psychiatry and neurology: A systematic review and meta-analysis di Janna N. de Boer, Alban Voppel, Marieke J.H. Begemann, Hugo G. Schnack, Frank Wijnen, Iris E. Sommer

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Mapping higher-order relations between brain structure and function with embedded vector representations of connectomes di Gideon Rosenthal, František Váša, Alessandra Griffa, Patric Hagmann, Enrico Amico, Joaquín Goñi, Galia Avidan, Olaf Sporns

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Recurrent Neural Network for Predicting Transcription Factor Binding Sites di Zhen Shen, Wenzheng Bao, De-Shuang Huang

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Using word embeddings to expand terminology of dietary supplements on clinical notes di Yadan Fan, Serguei Pakhomov, Reed McEwan, Wendi Zhao, Elizabeth Lindemann, Rui Zhang

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A k-mer grammar analysis to uncover maize regulatory architecture di Maria Katherine Mejía‐Guerra, Edward S. Buckler

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PTPD: predicting therapeutic peptides by deep learning and word2vec di Chuanyan Wu, Rui Gao, Yusen Zhang, Yang De Marinis

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A hybrid structured deep neural network with Word2Vec for construction accident causes classification di Fan Zhang

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Modeling aspects of the language of life through transfer-learning protein sequences di Michael Heinzinger, Ahmed Elnaggar, Yu Wang, Christian Dallago, Dmitrii Nechaev, Florian Matthes, Burkhard Rost

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A Deep Learning Framework for Gene Ontology Annotations With Sequence- and Network-Based Information di Fuhao Zhang, Hong Song, Min Zeng, Fang‐Xiang Wu, Yaohang Li, Yi Pan, Min Li

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A content-based literature recommendation system for datasets to improve data reusability – A case study on Gene Expression Omnibus (GEO) datasets di Braja Gopal Patra, Vahed Maroufy, Babak Soltanalizadeh, Nan Deng, W. Jim Zheng, Kirk Roberts, Hulin Wu

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Application of Machine Learning and Word Embeddings in the Classification of Cancer Diagnosis Using Patient Anamnesis di Andrés Ramos Magna, Héctor Allende‐Cid, Carla Taramasco, Carlos Becerra, Rosa L. Figueroa

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Identifying and Predicting Intentional Self-Harm in Electronic Health Record Clinical Notes: Deep Learning Approach di Jihad S. Obeid, Jennifer Dahne, Sean Christensen, Samuel Howard, Tami Crawford, Lewis J. Frey, Tracy Stecker, Brian E. Bunnell

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Suicide Risk Assessment Using Machine Learning and Social Networks: a Scoping Review di Gema Castillo-Sánchez, Gonçalo Marques, Enrique Dorronzoro, Octavio Rivera-Romero, Manuel Franco, Isabel de la Torre Díez

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DNA sequences performs as natural language processing by exploiting deep learning algorithm for the identification of N4-methylcytosine di Abdul Wahab, Hilal Tayara, Zhenyu Xuan, Kil To Chong

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Spec2Vec: Improved mass spectral similarity scoring through learning of structural relationships di Florian Huber, Lars Ridder, Stefan Verhoeven, Jurriaan H. Spaaks, F. Diblen, Simon Rogers, Justin J. J. van der Hooft

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LSTM-PHV: prediction of human-virus protein–protein interactions by LSTM with word2vec di Sho Tsukiyama, Md Mehedi Hasan, Satoshi Fujii, Hiroyuki Kurata

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