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COVID-19 identification in chest X-ray images on flat and hierarchical classification scenarios [article]

Rodolfo M. Pereira, Diego Bertolini, Lucas O. Teixeira, Carlos N. Silla Jr., Yandre M. G. Costa
2020 arXiv   pre-print
As far as we know, we achieved the best nominal rate obtained for COVID-19 identification in an unbalanced environment with more than three classes.  ...  The proposed approach achieved a macro-avg F1-Score of 0.65 using a multi-class approach and a F1-Score of 0.89 for the COVID-19 identification in the hierarchical classification scenario.  ...  Joseph Paul Cohen from the University of Montreal for providing such a useful dataset of pneumonia images for the research community.  ... 
arXiv:2004.05835v3 fatcat:jxmnzemoznbuhpnqqkoqrnmcb4

COVID-19 identification in chest X-ray images on flat and hierarchical classification scenarios

Rodolfo M. Pereira, Diego Bertolini, Lucas O. Teixeira, Carlos N. Silla, Yandre M.G. Costa
2020 Computer Methods and Programs in Biomedicine  
As far as we know, the top identification rate obtained in this paper is the best nominal rate obtained for COVID-19 identification in an unbalanced environment with more than three classes.  ...  The proposed approach tested in RYDLS-20 achieved a macro-avg F1-Score of 0.65 using a multi-class approach and a F1-Score of 0.89 for the COVID-19 identification in the hierarchical classification scenario  ...  Acknowledgments We thank the Brazilian Research Support Agencies: Coordination for the Improvement of Higher Education Personnel (CAPES), National Council for  ... 
doi:10.1016/j.cmpb.2020.105532 pmid:32446037 pmcid:PMC7207172 fatcat:ivp2e2vqyrfu7a6eizjfibg67a

Cross‐spectral synergy and consonant identification

Thomas Ulrich Christiansen, Steven Greenberg
2008 Journal of the Acoustical Society of America  
for presentation of poster papers on various topics in acoustics.  ...  This paper provides an overview of a unique monitoring system used in England and Wales for tracking the sound insulation performance for 110 000 new build homes per annum.  ...  the literature.  ... 
doi:10.1121/1.2935680 fatcat:znwocm35unasharfwbcap5omim

Stance Detection

Dilek Küçük, Fazli Can
2020 ACM Computing Surveys  
Although stance detection is defined in different ways in different application settings, the most common definition is "automatic classification of the stance of the producer of a piece of text, towards  ...  Stance detection is a recent natural language processing topic with diverse application areas, and our survey article on this newly emerging topic will act as a significant resource for interested researchers  ...  ACKNOWLEDGMENTS The authors would like to thank the anonymous reviewers for their insightful comments.  ... 
doi:10.1145/3369026 fatcat:5fviqvi6o5by7p6pdfrgxub2vi

Landscape of Big Medical Data: A Pragmatic Survey on Prioritized Tasks [article]

Zhifei Zhang, Wanling Gao, Fan Zhang, Yunyou Huang, Shaopeng Dai, Fanda Fan, Jianfeng Zhan, Mengjia Du, Silin Yin, Longxin Xiong, Juan Du, Yumei Cheng, Xiexuan Zhou, Rui Ren (+2 others)
2019 arXiv   pre-print
In this paper, a group of life scientists, clinicians, computer scientists and engineers sit together to discuss several fundamental issues.  ...  Fourth, are there any benchmarks for measuring algorithms and systems for big medical data?  ...  In the past eight years, many volunteers have spent time in analyzing Chinese medicine ingredients in the Chinese medical literature and building structural files for each of the isolated compounds.  ... 
arXiv:1901.00642v1 fatcat:fak46q7bgzesll6y4h7i6mcysi

Neural Natural Language Processing for Unstructured Data in Electronic Health Records: a Review [article]

Irene Li, Jessica Pan, Jeremy Goldwasser, Neha Verma, Wai Pan Wong, Muhammed Yavuz Nuzumlalı, Benjamin Rosand, Yixin Li, Matthew Zhang, David Chang, R. Andrew Taylor, Harlan M. Krumholz (+1 others)
2021 arXiv   pre-print
In this survey paper, we summarize current neural NLP methods for EHR applications.  ...  Recently, however, newer neural network and deep learning approaches to Natural Language Processing (NLP) have made considerable advances, outperforming traditional statistical and rule-based systems on  ...  Learning the semantics of these medical concepts can be helpful for other applications. A number of papers use deep models to learn such domainspecific embeddings.  ... 
arXiv:2107.02975v1 fatcat:nayhw7gadfdzrovycdkvzy75pi

Deep Learning Framework for Alzheimer's Disease Diagnosis via 3D-CNN and FSBi-LSTM

Chiyu Feng, Ahmed Elazab, Peng Yang, Tianfu Wang, Feng Zhou, Huoyou Hu, Xiaohua Xiao, Baiying Lei
2019 IEEE Access  
in the literature.  ...  However, due to the limited availability of these imaging data, it is still challenging to effectively use CNNs for AD diagnosis. Toward this end, we design a novel deep learning framework.  ...  COMPARISION WITH OTHER DEEP LEARNING MODEL TABLE 5 . 5 Algorithm comparisons for AD vs. NC classification(%). TABLE 6 . 6 Algorithm comparisons for pMCI vs. NC classification(%).  ... 
doi:10.1109/access.2019.2913847 fatcat:poa2tr2ge5dfvjrszzafcekndi

Handwritten Optical Character Recognition (OCR): A Comprehensive Systematic Literature Review (SLR)

Jamshed Memon, Maira Sami, Rizwan Ahmed Khan, Mueen Uddin
2020 IEEE Access  
During last decade, researchers have used artificial intelligence / machine learning tools to automatically analyze handwritten and printed documents in order to convert them into electronic format.  ...  In this Systematic Literature Review (SLR) we collected, synthesized and analyzed research articles on the topic of handwritten OCR (and closely related topics) which were published between year 2000 to  ...  Lately, the research in the domain of optical character recognition has moved towards a deep learning approach [189] , [190] with little emphasis on handcrafted features.  ... 
doi:10.1109/access.2020.3012542 fatcat:f5bfni5kbfhf3i63lvv3t6pena

Feature Evaluation of Emerging E-Learning Systems Using Machine Learning: An Extensive Survey

Shabnam Mohamed Aslam, Abdul Khader Jilani, Jabeen Sultana, Laila Almutairi
2021 IEEE Access  
The literature review methodology is to review the cross sectional impacts of e-learning and Machine learning algorithms from existing literatures from the year 1993 to 2020 and to assess the essentialness  ...  to predict the input and output parameters of e-learning models and it is found that Fuzzy C Means, Deep Learning algorithms are producing better results for Big Data sets.  ...  SELECTION OF STUDIES Totally 300 papers are fetched through search engines, out of which 121 papers has been identified to review the e-learning features and evaluation.  ... 
doi:10.1109/access.2021.3077663 fatcat:avwqkzxvufauvjjyebbm3twnpe

WearableDL: Wearable Internet-of-Things and Deep Learning for Big Data Analytics—Concept, Literature, and Future

Aras R. Dargazany, Paolo Stegagno, Kunal Mankodiya
2018 Mobile Information Systems  
Deep learning (DL) has recently gained popularity due to its ability to (1) scale to the big data size (scalability); (2) learn the feature engineering by itself (no manual feature extraction or hand-crafted  ...  features) in an end-to-end fashion; and (3) offer accuracy or precision in learning raw unlabeled/labeled (unsupervised/supervised) data.  ...  Fig. 3 . 3 Comparing AI and brain along with machine learning vs deep learning vs cortical learning.  ... 
doi:10.1155/2018/8125126 fatcat:ty3a7n4in5aahbqyl7wum5vonq

Clinical Applications of Artificial Intelligence—An Updated Overview

Ștefan Busnatu, Adelina-Gabriela Niculescu, Alexandra Bolocan, George E. D. Petrescu, Dan Nicolae Păduraru, Iulian Năstasă, Mircea Lupușoru, Marius Geantă, Octavian Andronic, Alexandru Mihai Grumezescu, Henrique Martins
2022 Journal of Clinical Medicine  
Moreover, a diverse repertoire of methods can be chosen towards creating performant models for use in medical applications, ranging from disease prediction, diagnosis, and prognosis to opting for the most  ...  Thus, this work presents AI clinical applications in a comprehensive manner, discussing the recent literature studies classified according to medical specialties.  ...  The choice of the included medical specialties was based on the available literature data, as other areas were not as explored in recent years or remained at the level of hypothesis/opinion papers.  ... 
doi:10.3390/jcm11082265 pmid:35456357 pmcid:PMC9031863 fatcat:mtzdrc7nyzgbjeyou3h4cuso7a

Face Recognition: A Novel Multi-Level Taxonomy based Survey [article]

Alireza Sepas-Moghaddam, Fernando Pereira, Paulo Lobato Correia
2019 arXiv   pre-print
The paper concludes with a discussion on current algorithmic and application related challenges which may define future research directions for face recognition.  ...  In a world where security issues have been gaining growing importance, face recognition systems have attracted increasing attention in multiple application areas, ranging from forensics and surveillance  ...  Fusion at feature and score levels are the most commonly used approaches in the biometric literature.  ... 
arXiv:1901.00713v1 fatcat:ofks5jqf6fca3e4l27nph6eiri

Woody plants of Utah: a field guide with identification keys to native and naturalized trees, shrubs, cacti, and vines

2012 ChoiceReviews  
All rights reserved Manufactured in the United States of America Cover design by Dan Miller ISBN: 978-0-87421-928-9 (paper) ISBN: 978-0-87421-929-6 (e-book) Library of Congress Cataloging-in-Publication  ...  The application of humor as a mediating device has not gone unnoticed in stigma literature.  ...  In medical anthropology these two features are designated disease and illness.  ... 
doi:10.5860/choice.49-6885 fatcat:lg4qxaxyovbz7ify3nsgk2lx3i

Molecular Genetic Studies of Gene Identification for Osteoporosis: The 2009 Update

Xiang-Hong Xu, Shan-Shan Dong, Yan Guo, Tie-Lin Yang, Shu-Feng Lei, Christopher J. Papasian, Ming Zhao, Hong-Wen Deng
2010 Endocrine reviews  
Our previously published reviews have comprehensively summarized the progress of molecular genetic studies of gene identification for osteoporosis and have covered the data available to the end of September  ...  Osteoporosis is a complex human disease that results in increased susceptibility to fragility fractures.  ...  Boonen is senior clinical investigator of the Fund for Scientific Research, Flanders, Belgium (F.W.O.-Vlaanderen) and holder of the Leuven University Chair in Gerontology and Geriatrics.  ... 
doi:10.1210/er.2009-0032 pmid:20357209 pmcid:PMC3365849 fatcat:sv2hwzp22naerftn55ojqapg4m

Developing Future Human-Centered Smart Cities: Critical Analysis of Smart City Security, Interpretability, and Ethical Challenges [article]

Kashif Ahmad, Majdi Maabreh, Mohamed Ghaly, Khalil Khan, Junaid Qadir, Ala Al-Fuqaha
2021 arXiv   pre-print
In this paper, we analyze and explore key challenges including security, robustness, interpretability, and ethical (data and algorithmic) challenges to a successful deployment of AI in human-centric applications  ...  We believe such rigorous analysis will provide a baseline for future research in the domain.  ...  Explainable Features Another important aspect of explainable ML is explainable feature engineering, which aims for the identification of features influencing an ML model's decision.  ... 
arXiv:2012.09110v4 fatcat:yxh5tvpehbgldcblweoovbvdsq
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