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Ensuring the Robustness and Reliability of Data-Driven Knowledge Discovery Models in Production and Manufacturing [article]

Shailesh Tripathi
2020 arXiv   pre-print
for data mining (CRISP-DM).  ...  data experts and business experts because of the limitations of data-driven knowledge discovery models.  ...  In general, feature learning enhances the efficiency of regression and classification models used for predictive maintenance and product quality classification.  ... 
arXiv:2007.14791v1 fatcat:difcf5l765bvljormncbhh3zca

New on the market

2004 Nature Biotechnology  
It features enhanced ease-of-use and workflow automation, using wizards to guide the incorporation of external components and the creation of complex workflows.  ...  Drug discovery automation InforSense's Knowledge Discovery Environment 1.9 is designed to create, capture and manage valuable process knowledge for high-throughput discovery.  ... 
doi:10.1038/nbt0304-351 fatcat:52nptpf42rfklmnfmuktw2nghy

A Unified Review of Deep Learning for Automated Medical Coding [article]

Shaoxiong Ji and Wei Sun and Hang Dong and Honghan Wu and Pekka Marttinen
2022 arXiv   pre-print
Automated medical coding, an essential task for healthcare operation and delivery, makes unstructured data manageable by predicting medical codes from clinical documents.  ...  ., encoder modules for text feature extraction, mechanisms for building deep encoder architectures, decoder modules for transforming hidden representations into medical codes, and the usage of auxiliary  ...  Joint embedding of Wikipedia and clinical notes introduces external knowledge sources to medical coding models.  ... 
arXiv:2201.02797v1 fatcat:ajl6uq6mkzdo3j2trmfy5ceypq

Lecturer Sociometric Badge as Digital Platform in Indonesia Higher Education Institutions From Organizational Effectiveness Perspective

Astadi Pangarso
2019 Figshare  
p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 9.0px Helvetica} This paper objective is to explain conceptually about the idea to use sociometric badge for lecturer generally in Indonesia higher education  ...  Every lecturer's roles have different interactions with different parties (internally and externally).  ...  If the two effectiveness models is associated with the university as an organization's, lecturers as knowledge worker tends to be connected in quadrants of human relations internal models and process models  ... 
doi:10.6084/m9.figshare.9872969 fatcat:cg6kbssrt5cxxm2gibkydiyp7y

Applying single-image super-resolution to enhancment of deep-water bathymetry

Kristen Nock, David Bonanno, Paul Elmore, Leslie Smith, Vicki Ferrini, Fred Petry
2019 Heliyon  
We present research using single-image super-resolution (SISR) algorithms to enhance knowledge of the seafloor using the 1-minute GEBCO 2014 grid when 100m grids from high-resolution sonar systems are  ...  available for training.  ...  The external validation experiment of using NEPR to predict SEPR is the only external upscaling case where the SISR methods provide enhanced skill versus interpolation.  ... 
doi:10.1016/j.heliyon.2019.e02570 pmid:31687485 pmcid:PMC6820091 fatcat:fdw4irlc6vflha6evlmvizshd4

AZOrange - High performance open source machine learning for QSAR modeling in a graphical programming environment

Jonna C Stålring, Lars A Carlsson, Pedro Almeida, Scott Boyer
2011 Journal of Cheminformatics  
The automated work flow relies upon the customization of the machine learning algorithms and a generalized, automated model hyper-parameter selection process.  ...  Hence, there is a demand for computationally efficient machine learning algorithms, easily available to researchers without extensive machine learning knowledge.  ...  JCS, PA and LAC together explored the possibilities for using a pattern search algorithm for generalized and automated model hyper-parameter selection.  ... 
doi:10.1186/1758-2946-3-28 pmid:21798025 pmcid:PMC3158423 fatcat:hxnsmgkmfvcxvog3pcy5qfo7qm

Using Digital Twins and Intelligent Cognitive Agencies to Build Platforms for Automated CxO Future of Work [article]

John-Thones Amenyo
2018 arXiv   pre-print
In this paper, design principles based on computational thinking are used to engineer the architecture and infrastructure for such CxO automation platforms.  ...  Building platforms for CxO automation is challenging.  ...  Computational thinking and Computational Models of Human Performance Augmentation and Externalized Enhancement.  ... 
arXiv:1808.07627v1 fatcat:s74bfjresbc3lipkgcrkzsrobe

Edge: Enriching Knowledge Graph Embeddings with External Text [article]

Saed Rezayi, Handong Zhao, Sungchul Kim, Ryan A. Rossi, Nedim Lipka, Sheng Li
2021 arXiv   pre-print
Given an original knowledge graph, we first generate a rich but noisy augmented graph using external texts in semantic and structural level.  ...  Previous work has partially addressed this issue by enriching knowledge graph entities based on "hard" co-occurrence of words present in the entities of the knowledge graphs and external text, while we  ...  Using external source of information introduces new sets of features that enhance the quality of embeddings.  ... 
arXiv:2104.04909v1 fatcat:dvr7kbcerbaphj4vsdlo3uzi4u

Machine-learning analysis of contrast-enhanced CT radiomics predicts recurrence of hepatocellular carcinoma after resection: A multi-institutional study

Gu-Wei Ji, Fei-Peng Zhu, Qing Xu, Ke Wang, Ming-Yu Wu, Wei-Wei Tang, Xiang-Cheng Li, Xue-Hao Wang
2019 EBioMedicine  
We employed Cox modeling to build predictive models. The models were then validated using an internal dataset of 107 patients and an external dataset of 153 patients from Institution 2 and 3.  ...  Using the machine-learning framework, we identified a three-feature signature that demonstrated favorable prediction of HCC recurrence across all datasets, with C-index of 0.633-0.699.  ...  Inter-reader agreement for the two semantic features that were incorporated into predictive models was excellent (k=0.906 for liver cirrhosis and 0.880 for tumor margin).  ... 
doi:10.1016/j.ebiom.2019.10.057 pmid:31735556 pmcid:PMC6923482 fatcat:4vutbmk3wzd37bpkdrq53rdote

Web to world: predicting transitions from self-diagnosis to the pursuit of local medical assistance in web search

Ryen W White, Eric Horvitz
2010 AMIA Annual Symposium Proceedings  
We build models that predict the transition from searches on initial common symptoms to queries pursuing local medical expertise, using evidence about a user's stream of queries, the content on reviewed  ...  Many people turn to the Web for self-diagnosis and healthcare assessment based on limited knowledge of signs, symptoms, and disorders.  ...  We characterized aspects of resource usage and developed models to predict transitions to queries for external resources using features of the current Web page, the session, and aspects of the user's medical  ... 
pmid:21347105 pmcid:PMC3041420 fatcat:eoipvegdxvc7zefvh3syet6tw4

Ensuring the Robustness and Reliability of Data-Driven Knowledge Discovery Models in Production and Manufacturing

Shailesh Tripathi, David Muhr, Manuel Brunner, Herbert Jodlbauer, Matthias Dehmer, Frank Emmert-Streib
2021 Frontiers in Artificial Intelligence  
Overall, such a customizable GCRISP-DS framework provides an enhancement for model improvements and reusability by minimizing robustness-issues.  ...  However, the practical application of robust industry-specific data-driven knowledge discovery models faces multiple data- and model development-related issues.  ...  In general, feature learning enhances the efficiency of regression and classification models used for predictive maintenance and product quality classification.  ... 
doi:10.3389/frai.2021.576892 fatcat:zyf6bk2mhvd2fnoy7hpdhoagtu

Industrial Cyber Physical Systems Supported by Distributed Advanced Data Analytics [chapter]

Jonas Queiroz, Paulo Leitão, Eugénio Oliveira
2017 Studies in Computational Intelligence  
In this context, the data is a valuable asset that can support the smart factory features through the use of Big Data and advanced analytics approaches.  ...  The industry digitization is transforming its business models, organizational structures and operations, mainly promoted by the advances and the mass utilization of smart methods, devices and products,  ...  Also for the PAs different data analysis models were developed for the prediction of renewable energy production, using historical data, as well as external data from weather forecasts.  ... 
doi:10.1007/978-3-319-51100-9_5 fatcat:xmixhokz2bad7iv4r4prsoq4fm

New Insights from Old Data: Multimodal Classification of Schizophrenia using Automated Deep Learning Configurations [article]

Gagana B
2020 bioRxiv   pre-print
high dimensional feature space with very little data.  ...  There is, hence, a need for objective systems that can classify Schizophrenia despite challenges such as overlapping symptomatic factors, diverse internal clinical manifestations, and complex diagnostic  ...  While most of the tools used in the study enable external augmentations and interpretable enhancements, few internally support interpretability.  ... 
doi:10.1101/2020.11.02.364976 fatcat:ml6smj7525denjyar6yxiakuoe

Extending the Technology Acceptance Model to assess automation

Mahtab Ghazizadeh, John D. Lee, Linda Ng Boyle
2011 Cognition, Technology & Work  
We propose the Automation Acceptance Model (AAM) to draw upon the IS and CE perspectives and take into account the dynamic and multi-level nature of automation use, highlighting the influence of use on  ...  user acceptance of technology, using the Technology Acceptance Model (TAM).  ...  Acknowledgments The authors would like to thank the members of the Cognitive Systems Laboratory (CSL) at the University of Wisconsin-Madison, for their helpful comments on earlier versions of this manuscript  ... 
doi:10.1007/s10111-011-0194-3 fatcat:wv4nibsfdnbqfaxknqpfynaere

Automated deep learning design for medical image classification by health-care professionals with no coding experience: a feasibility study

Livia Faes, Siegfried K Wagner, Dun Jack Fu, Xiaoxuan Liu, Edward Korot, Joseph R Ledsam, Trevor Back, Reena Chopra, Nikolas Pontikos, Christoph Kern, Gabriella Moraes, Martin K Schmid (+5 others)
2019 The Lancet Digital Health  
In an external validation using the Edinburgh Dermofit Library dataset, the automated deep learning model showed an AUPRC of 0·47, with a sensitivity of 49% and a positive predictive value of 52%.  ...  The availability of automated deep learning platforms provide an opportunity for the medical community to enhance their understanding in model development and evaluation.  ...  LF and SW trained the automated deep learning models and collected the data, which were analysed by LF, SKW, DJF, LMB, and PAK.  ... 
doi:10.1016/s2589-7500(19)30108-6 pmid:33323271 fatcat:l4y4gmsm5bh35kddwfkn2y3lqa
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