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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 Hits 1 – 20 of 65 1 Using Machine Learning for Pharmacovigilance: A Systematic Review Patrick Pilipiec; Marcus Liwicki; András Bota In: Pharmaceutics; Volume 14; Issue 2; Pages: 266 (2022) BASE Show details 2 Vec2Dynamics: A Temporal Word Embedding Approach to Exploring the Dynamics of Scientific Keywords—Machine Learning as a Case Study Amna Dridi; Mohamed Medhat Gaber; Raja Muhammad Atif Azad; Jagdev Bhogal In: Big Data and Cognitive Computing; Volume 6; Issue 1; Pages: 21 (2022) BASE Show details 3 Arc-Eager Construction Provides Learning Advantage Beyond Stack Management Barnett, Phillip A. - : eScholarship, University of California, 2021 BASE Show details 4 Language and Reasoning by Entropy Fractals Daniela López De Luise In: Signals ; Volume 2 ; Issue 4 ; Pages 44-770 (2021) BASE Show details 5 Learning meaning representations for text generation with deep generative models ... Cao, Kris. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 6 Modelling speaker adaptation in second language learner dialogue ... Sinclair, Arabella Jane. - : The University of Edinburgh, 2020 BASE Show details 7 Towards Programming in Natural Language: Learning New Functions from Spoken Utterances ... Weigelt, Sebastian; Steurer, Vanessa; Hey, Tobias. - : World Scientific Publishing, 2020 BASE Show details 8 Модели и методы анализа тональности в текстах на башкирском языке ... : Models and methods for sentiment analysis of texts in Bashkir language ... Сулейманов, А.К.; Шарипова, М.А.; Сметанина, О.Н.. - : Воронежский институт высоких технологий, 2020 BASE Show details 9 Pathways to the Native Storyteller: a method to enable computational story understanding Kehinde, Aramide O. In: College of Computing and Digital Media Dissertations (2020) BASE Show details 10 Towards Programming in Natural Language: Learning New Functions from Spoken Utterances Hey, Tobias; Weigelt, Sebastian; Steurer, Vanessa... In: International journal of semantic computing, 14 (2), 249–272 ; ISSN: 1793-351X, 1793-7108 (2020) BASE Show details 11 Modelling speaker adaptation in second language learner dialogue Sinclair, Arabella Jane. - : The University of Edinburgh, 2020 BASE Show details 12 Learning meaning representations for text generation with deep generative models Cao, Kris. - : University of Cambridge, 2019. : Department of Computer Science and Technology, 2019. : Clare, 2019 BASE Show details 13 Learnability and Overgeneration in Computational Syntax Hao, Yiding In: Proceedings of the Society for Computation in Linguistics (2019) BASE Show details 14 Neural networks for narrative continuation ... Roemmele, Melissa Susan. - : University of Southern California Digital Library (USC.DL), 2018 BASE Show details 15 Describing and Classifying Post-Mortem Content on Social Media Jiang, Jialun; Brubaker, Jed In: Proceedings of the International AAAI Conference on Web and Social Media; Vol. 12 No. 1 (2018): Twelfth International AAAI Conference on Web and Social Media ; 2334-0770 ; 2162-3449 (2018) BASE Show details 16 hr500k – A Reference Training Corpus of Croatian. Erjavec, Tomaž; Ljubešić, Nikola; Klubicka, Filip... In: Conference papers (2018) BASE Show details 17 Comparative analysis of algorithmic approaches for auto-coding with ICD-10-AM and ACHI Kaur, Rajvir (S33301); Ginige, Jeewani A. (R12232). - : Netherlands, IOS Press, 2018 Abstract: Clinical coding is done using ICD-10-AM (International Classification of Diseases, version 10, Australian Modification) and ACHI (Australian Classification of Health Interventions) in acute and sub-acute hospitals in Australia for funding, insurance claims processing and research. The task of assigning a code to an episode of care is a manual process. This has posed challenges due to increase set of codes, the complexity of care episodes, and large training and recruitment costs of clinical coders. Use of Natural Language Processing (NLP) and Machine Learning (ML) techniques is considered as a solution to this problem. This paper carries out a comparative analysis on a selected set of NLP and ML techniques to identify the most efficient algorithm for clinical coding based on a set of standard metrics: precision, recall, F-score, accuracy, Hamming loss and Jaccard similarity. Keyword: 080702 - Health Informatics; Australia; computational linguistics; data processing; diagnosis related groups; machine learning; medical records URL: https://doi.org/10.3233/978-1-61499-890-7-73 http://handle.westernsydney.edu.au:8081/1959.7/uws:49529 BASE Hide details 18 Modeling common sense knowledge via scripts ... : Modellierung von Weltwissen mit Skripten ... Modi, Ashutosh. - : Universität des Saarlandes, 2017 BASE Show details 19 Filtering Tweets for Social Unrest ... Mishler, Alan; Wonus, Kevin; Chambers, Wendy. - : Digital Repository at the University of Maryland, 2017 BASE Show details 20 Modeling common sense knowledge via scripts ; Modellierung von Weltwissen mit Skripten Modi, Ashutosh. - 2017 BASE Show details Page: 1 2 3 4

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