AIMC Topic: Problem Solving
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DR.BENCH: Diagnostic Reasoning Benchmark for Clinical Natural Language Processing.
Journal of biomedical informatics
Jan 25, 2023
The meaningful use of electronic health records (EHR) continues to progress in the digital era with clinical decision support systems augmented by artificial intelligence. A priority in improving provider experience is to overcome information overloa...
Emulating future neurotechnology using magic.
Consciousness and cognition
Dec 23, 2022
Recent developments in neuroscience and artificial intelligence have allowed machines to decode mental processes with growing accuracy. Neuroethicists have speculated that perfecting these technologies may result in reactions ranging from an invasion...
Self-regulated learning and the future of diagnostic reasoning education.
Diagnosis (Berlin, Germany)
Dec 8, 2022
Diagnostic reasoning is a foundational ability of health professionals. The goal of enhancing clinical reasoning education is improved diagnostic accuracy and reduced diagnostic error. In order to do so, health professions educators need not only hel...
On a Finitely Activated Terminal RNN Approach to Time-Variant Problem Solving.
IEEE transactions on neural networks and learning systems
Nov 30, 2022
This article concerns with terminal recurrent neural network (RNN) models for time-variant computing, featuring finite-valued activation functions (AFs), and finite-time convergence of error variables. Terminal RNNs stand for specific models that adm...
Utilizing artificial intelligence to solving time - cost - quality trade-off problem.
Scientific reports
Nov 22, 2022
This study presents the Slime Mold Algorithm (SMA) to solve the time-cost-quality trade-off problem in a construction project. The proposed SMA is a flexible and efficient algorithm in exploration and exploitation to reach the best optimal solution t...
Deep Learning Model for the Image Fusion and Accurate Classification of Remote Sensing Images.
Computational intelligence and neuroscience
Nov 22, 2022
Deep learning is widely used for the classification of images that have various attributes. Image data are used to extract colour, texture, form, and local features. These features are combined in feature-level image fusion to create a merged remote ...
Multiagent-Based Data Presentation Mechanism for Multifaceted Analysis in Network Management Tasks.
Sensors (Basel, Switzerland)
Nov 15, 2022
Although network management tasks are highly automated using big data and artificial intelligence technologies, when an unforeseen cybersecurity problem or fault scenario occurs, administrators sometimes directly analyze system data to make a heurist...
Capturing advanced human cognitive abilities with deep neural networks.
Trends in cognitive sciences
Nov 2, 2022
How can artificial neural networks capture the advanced cognitive abilities of pioneering scientists? I suggest they must learn to exploit human-invented tools of thought and human-like ways of using them, and must engage in explicit goal-directed pr...
Neurodynamics-driven portfolio optimization with targeted performance criteria.
Neural networks : the official journal of the International Neural Network Society
Oct 28, 2022
This paper addresses portfolio selection with targeted performance criteria via neurodynamic optimization. Five portfolio optimization problems are formulated with a variable weight to maximize five risk-adjusted performance criteria in Markowitz's m...
A Barrier Varying-Parameter Dynamic Learning Network for Solving Time-Varying Quadratic Programming Problems With Multiple Constraints.
IEEE transactions on cybernetics
Aug 18, 2022
Many scientific research and engineering problems can be converted to time-varying quadratic programming (TVQP) problems with constraints. Thus, TVQP problem solving plays an important role in practical applications. Many existing neural networks, su...
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