AIMC Topic: Uncertainty

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Artificial neural network detects human uncertainty.

Chaos (Woodbury, N.Y.) Mar 1, 2018
Artificial neural networks (ANNs) are known to be a powerful tool for data analysis. They are used in social science, robotics, and neurophysiology for solving tasks of classification, forecasting, pattern recognition, etc. In neuroscience, ANNs allo...
Neural Networks, Computer Female Reproducibility of Results Humans Signal Processing, Computer-Assisted Uncertainty Magnetoencephalography Adult Male
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Building Bayesian Networks from Causal Rules.

Studies in health technology and informatics Jan 1, 2018
Bayesian Networks (BNs) are often used for designing diagnosis decision support systems. They are a well-established method for reasoning under uncertainty and making inferences. But, eliciting the probabilities can be tedious and time-consuming espe...
Software Bayes Theorem Probability Humans Expert Systems Diagnosis Uncertainty
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Application of Fuzzy Set/Qualitative Comparative Analysis to Public Participation Projects in Support of the EU Water Framework Directive.

Water environment research : a research publication of the Water Environment Federation Jan 1, 2018
  This study analyzes the level of satisfaction of stakeholders in the public participation process (PPP) of water resources management, which is mandatory according to the EU Water Framework Directive (WFD). The methodology uses a fuzzy set/qualitat...
Fuzzy Logic Water Resources Community Participation Uncertainty European Union Conservation of Natural Resources Humans Waste Disposal, Fluid
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Using uncertainty to link and rank evidence from biomedical literature for model curation.

Bioinformatics (Oxford, England) Dec 1, 2017
MOTIVATION: In recent years, there has been great progress in the field of automated curation of biomedical networks and models, aided by text mining methods that provide evidence from literature. Such methods must not only extract snippets of text t...
Machine Learning Publications Data Mining Uncertainty
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["Handle with care": about the potential unintended consequences of oracular artificial intelligence systems in medicine.].

Recenti progressi in medicina Oct 1, 2017
Decisional support systems based on machine learning (ML) in medicine are gaining a growing interest as some recent articles have highlighted the high diagnostic accuracy exhibited by these systems in specific medical contexts. However, it is implaus...
Decision Support Systems, Clinical Uncertainty Artificial Intelligence Biomedical Research Humans
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Artificial intelligence: A social spin on language analysis.

Nature May 10, 2017
Bullying Agonistic Behavior Uncertainty Verbal Behavior Crowdsourcing Software Search Engine Humans Language Neural Networks, Computer Machine Learning Social Media Data Mining Support Vector Machine
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River flood prediction using fuzzy neural networks: an investigation on automated network architecture.

Water science and technology : a journal of the International Association on Water Pollution Research Apr 1, 2017
Urban floods are one of the most devastating natural disasters globally and improved flood prediction is essential for better flood management. Today, high-resolution real-time datasets for flood-related variables are widely available. These data can...
Canada Models, Theoretical Neural Networks, Computer Rivers Algorithms Disasters Floods Uncertainty Fuzzy Logic
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Can we open the black box of AI?

Nature Oct 6, 2016
Humans Creativity Neural Networks, Computer Physics Astronomy Datasets as Topic Machine Learning Robotics Thinking Uncertainty
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Heart beat characterization from ballistocardiogram signals using extended functions of multiple instances.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
A multiple instance learning (MIL) method, extended Function of Multiple Instances (eFUMI), is applied to ballistocardiogram (BCG) signals produced by a hydraulic bed sensor. The goal of this approach is to learn a personalized heartbeat "concept" fo...
Transducers Heart Rate Ballistocardiography Humans Uncertainty Machine Learning
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Robotic path-finding in inverse treatment planning for stereotactic radiosurgery with continuous dose delivery.

Medical physics Aug 1, 2016
PURPOSE: Continuous dose delivery in radiation therapy treatments has been shown to decrease total treatment time while improving the dose conformity and distribution homogeneity over the conventional step-and-shoot approach. The authors develop an i...
Robotics Radiotherapy Planning, Computer-Assisted Algorithms Uncertainty Radiotherapy Dosage Radiosurgery
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