Filters








1,447 Hits in 11.8 sec

Automatic Recommendation of Prognosis Measures for Mechanical Components based on Massive Text Mining

Jorge Martinez
2018 Figshare  
In this work, we propose a solution based on massive text mining for automatically suggesting prognosis activities concerning mechanical components.  ...  Existing solutions based on ontological models have proven to be appropriate for fault diagnosis, but they fail when suggesting activities leading to a successful prognosis of mechanical components.  ...  , Innovation and Technology, the Federal Ministry of Science, Research and Economy, and the Province of Upper Austria in the frame of the COMET center Software Competence Center Hagenberg (SCCH).  ... 
doi:10.6084/m9.figshare.6634703.v1 fatcat:hh2hohanvrgkxjlo3f6xk5ta6e

Dynamic Clinical Data Mining: Search Engine-Based Decision Support

Leo Anthony Celi, Andrew J Zimolzak, David J Stone
2014 JMIR Medical Informatics  
interventions and prognosis, based on prior outcomes.  ...  The research world is undergoing a transformation into one in which data, on massive levels, is freely shared.  ...  Acknowledgments We would like to thank Marie Csete, MD, PhD; and Daniel Stone, PhD, for their helpful comments. Conflicts of Interest None declared.  ... 
doi:10.2196/medinform.3110 pmid:25600664 pmcid:PMC4288074 fatcat:2aqthyo5dnbqdlxkae7dx3nofy

AI and Big Data in Healthcare: Towards a More Comprehensive Research Framework for Multimorbidity

Ljiljana Trtica Majnarić, František Babič, Shane O'Sullivan, Andreas Holzinger
2021 Journal of Clinical Medicine  
This may include, for example, prediction, correlation, and classification problems based on multiple interaction factors.  ...  Multimorbidity refers to the coexistence of two or more chronic diseases in one person. Therefore, patients with multimorbidity have multiple and special care needs.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/jcm10040766 pmid:33672914 fatcat:tghkcoydh5bavoydi2dh2bwvwq

Analytics for the Internet of Things: A Survey [article]

Eugene Siow, Thanassis Tiropanis, Wendy Hall
2018 arXiv   pre-print
This taxonomy provides us with insights on the appropriateness of analytical techniques, which in turn shapes a survey of enabling technology and infrastructure for IoT analytics.  ...  This article reviews work in the IoT and big data analytics from the perspective of their utility in creating efficient, effective and innovative applications and services for a wide spectrum of domains  ...  The analytics techniques include text classification using Naive Bayes, a top-K recommendation engine based on similarity and a Random Forests classifier to categorise data as part of Decision Support  ... 
arXiv:1807.00971v1 fatcat:jwywwwhbznfprmpi4xvwoag3zy

Analytics for the Internet of Things

Eugene Siow, Thanassis Tiropanis, Wendy Hall
2018 ACM Computing Surveys  
This taxonomy provides us with insights on the appropriateness of analytical techniques, which in turn shapes a survey of enabling technology and infrastructure for IoT analytics.  ...  This article reviews work in the IoT and big data analytics from the perspective of their utility in creating efficient, effective and innovative applications and services for a wide spectrum of domains  ...  The analytics techniques include text classification using Naive Bayes, a top-K recommendation engine based on similarity and a Random Forests classifier to categorise data as part of Decision Support  ... 
doi:10.1145/3204947 fatcat:m5qpzmych5gkhb5nw2xfoezvpm

Clinical big data and deep learning: Applications, challenges, and future outlooks

Ying Yu, Min Li, Liangliang Liu, Yaohang Li, Jianxin Wang
2019 Big Data Mining and Analytics  
The explosion of digital healthcare data has led to a surge of data-driven medical research based on machine learning.  ...  Firstly, based on the analysis of the characteristics of clinical data, various types of clinical data (e.g., medical images, clinical notes, lab results, vital signs, and demographic informatics) are  ...  [48] combined Doc2vec and CNN for ICD-9 automatic coding based on MIMIC datasets. Recently, Guo et al.  ... 
doi:10.26599/bdma.2019.9020007 dblp:journals/bigdatama/YuLLLW19 fatcat:72fi4naporetvlq4unvlypbzne

Improving Decision Support Systems with Data Mining Techniques" [chapter]

Adela Bra, Ion Lungu
2012 Advances in Data Mining Knowledge Discovery and Applications  
Acknowledgement This paper is a result of the research project PN II, TE Program, Code 332: "Informatics Solutions for decision making support in the uncertain and unpredictable environments in order to  ...  integrate them within a grid network", financed within the framework of People research program.  ...  based on existing ones;  Models for multimedia (TEXT) and bio-informatics (BLAST).  ... 
doi:10.5772/47788 fatcat:s6zfk4ze7vd2daivvsomdtucl4

Healthcare Applications of Artificial Intelligence and Analytics: A Review and Proposed Framework

Sabrina Azzi, Stéphane Gagnon, Alex Ramirez, Gregory Richards
2020 Applied Sciences  
Healthcare is considered as one of the most promising application areas for artificial intelligence and analytics (AIA) just after the emergence of the latter.  ...  patient needs in various healthcare contexts, especially for chronic care patients, who present the most complex comorbidities and care needs.  ...  Conflicts of Interest: The authors declare no conflict of interest. Appl. Sci. 2020, 10, 6553  ... 
doi:10.3390/app10186553 doaj:b03bcc6944824d55825a0d6daa7f3459 fatcat:vztt35io3nhefml6ljsgmtebj4

The Role of Artificial Intelligence (AI) in Condition Monitoring and Diagnostic Engineering Management (COMADEM): A Literature Survey

B. K. Nagaraja Rao
2021 American Journal of Artificial Intelligence  
AI techniques such as, knowledge based systems, expert systems, artificial neural networks, genetic algorithms, fuzzy logic, casebased reasoning and any combination of these techniques (hybrid systems)  ...  the proactive maintenance management of industrial assets.  ...  Zhe Li et al [101] investigated fault diagnosis and prognosis in machine centers based on data mining approaches to formulate a systematic approach and obtain knowledge for predictive maintenance in  ... 
doi:10.11648/j.ajai.20210501.12 fatcat:gvplqmpqubdw3pquik5eavux5u

BIG DATA for Healthcare: A Survey

Safa Bahri, Nesrine Zoghlami, Mourad Abed, Joao Manuel R. S. Tavares
2019 IEEE Access  
This clinical data have been gathered up and interpreted by medical organizations in order to gain insights and knowledge useful for clinical decisions, drug recommendations, and better diagnoses, among  ...  This paper highlights the enormous impacts of big data on medical stakeholders, patients, physicians, pharmaceutical and medical operators, and healthcare insurers, and also reviews the different challenges  ...  of massive amount of data simpler and faster through its efficient and cost-effective mechanisms.  ... 
doi:10.1109/access.2018.2889180 fatcat:dzgmmkcuvfd23hepvlgv4tvxy4

Crowdsourcing in biomedicine: challenges and opportunities

Ritu Khare, Benjamin M. Good, Robert Leaman, Andrew I. Su, Zhiyong Lu
2015 Briefings in Bioinformatics  
mining crowd data and active crowdsourcing. • The studies are summarized based on the crowdsourcing platforms, such as labor markets, scientific games, wikis and community challenges. • Emerging themes  ...  Finally, we identify important emerging trends, opportunities and remaining challenges for future crowdsourcing research in biomedicine. • Recent crowdsourcing studies for biomedicine are categorized into  ...  Acknowledgment The authors are grateful to the anonymous reviewers for their insightful observations and helpful comments.  ... 
doi:10.1093/bib/bbv021 pmid:25888696 pmcid:PMC4719068 fatcat:e6avuxul5rhfzgdaywgvb3wte4

Temporal data representation, normalization, extraction, and reasoning: A review from clinical domain

Mohcine Madkour, Driss Benhaddou, Cui Tao
2016 Computer Methods and Programs in Biomedicine  
However, temporal data representation, normalization, extraction and reasoning are very important in order to mine such massive data and therefore for constructing the clinical timeline.  ...  Results-the main findings of this review is revealing the importance of time processing not only in constructing timelines and clinical decision support systems but also as a vital component of EHR data  ...  Acknowledgments This research is partially supported by the National Institutes of Health under Award Numbers R01LM011829 and R01GM103859.  ... 
doi:10.1016/j.cmpb.2016.02.007 pmid:27040831 pmcid:PMC4837648 fatcat:a75g25csqzdvlkfusbbgwmxigq

A Survey of Predictive Maintenance: Systems, Purposes and Approaches [article]

Yongyi Ran, Xin Zhou, Pengfeng Lin, Yonggang Wen, Ruilong Deng
2019 arXiv   pre-print
Furthermore, we provide a review of the existing approaches for fault diagnosis and prognosis in PdM systems that include three major subcategories: knowledge based, traditional Machine Learning (ML) based  ...  We make a brief review on the knowledge based and traditional ML based approaches applied in diverse industrial systems or components with a complete list of references, while providing a comprehensive  ...  However, most of the existing DLbased approaches only focus on the fault diagnosis and prognosis for a specific component.  ... 
arXiv:1912.07383v1 fatcat:vjunlhidqra7baucyl42ss45iy

What's the big deal about big data?

Nick Cercone, F'IEEE
2015 Big Data & Information Analytics  
This position paper is based on a major cooperative research and development proposal to form a Big Data Research, Analytics, and Information Network (BRAIN).  ...  areas of investigation.  ...  The support of Canada's Natural Sciences and Engineering Research Council (NSERC) and the Ontario Centres of Excellence is gratefully 70 NICK CERCONE, F'IEEE acknowledged for their encouragement and funding  ... 
doi:10.3934/bdia.2016.1.31 fatcat:wtdsmvgvvrfbjjui3v2cc56gbm

Deep learning in mental health outcome research: a scoping review

Chang Su, Zhenxing Xu, Jyotishman Pathak, Fei Wang
2020 Translational Psychiatry  
According to the application scenarios, we categorize these relevant articles into four groups: diagnosis and prognosis based on clinical data, analysis of genetics and genomics data for understanding  ...  Recently, artificial intelligence (AI) methods have been introduced to assist mental health providers, including psychiatrists and psychologists, for decision-making based on patients' historical data  ...  This is one reason why DL has achieved great success in the fields where a massive volume of data can be easily collected, such as computer vision and text mining.  ... 
doi:10.1038/s41398-020-0780-3 pmid:32532967 pmcid:PMC7293215 fatcat:gbdjszebnndt3j4todyw5k2scq
« Previous Showing results 1 — 15 out of 1,447 results