AIMC Topic:
Learning

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Back to the future: The return of cognitive functionalism.

The Behavioral and brain sciences Jan 1, 2017
The claims that learning systems must build causal models and provide explanations of their inferences are not new, and advocate a cognitive functionalism for artificial intelligence. This view conflates the relationships between implicit and explici...
Thinking Learning Cognition
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The architecture challenge: Future artificial-intelligence systems will require sophisticated architectures, and knowledge of the brain might guide their construction.

The Behavioral and brain sciences Jan 1, 2017
In this commentary, we highlight a crucial challenge posed by the proposal of Lake et al. to introduce key elements of human cognition into deep neural networks and future artificial-intelligence systems: the need to design effective sophisticated ar...
Neural Networks, Computer Artificial Intelligence Humans Learning Intelligence Brain
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Deep Diabetologist: Learning to Prescribe Hypoglycemic Medications with Recurrent Neural Networks.

Studies in health technology and informatics Jan 1, 2017
In healthcare, applying deep learning models to electronic health records (EHRs) has drawn considerable attention. This sequential nature of EHR data make them wellmatched for the power of Recurrent Neural Network (RNN). In this poster, we propose "D...
Learning Logistic Models Machine Learning Diabetes Mellitus Humans Clinical Decision-Making Hypoglycemic Agents Neural Networks, Computer
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Applying Risk Models on Patients with Unknown Predictor Values: An Incremental Learning Approach.

Studies in health technology and informatics Jan 1, 2017
In clinical practice, many patients may have unknown or missing values for some predictors, causing that the developed risk models cannot be directly applied on these patients. In this paper, we propose an incremental learning approach to apply a dev...
Humans Diabetes Mellitus, Type 2 Cluster Analysis Learning Risk Female Male Machine Learning Electronic Health Records
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Diagnostic Machine Learning Models for Acute Abdominal Pain: Towards an e-Learning Tool for Medical Students.

Studies in health technology and informatics Jan 1, 2017
Computer-aided learning systems (e-learning systems) can help medical students gain more experience with diagnostic reasoning and decision making. Within this context, providing feedback that matches students' needs (i.e. personalised feedback) is bo...
Decision Making Learning Abdominal Pain Feedback Students, Medical Humans Education, Medical, Undergraduate Clinical Competence Machine Learning
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Deep Learning: A Primer for Radiologists.

Radiographics : a review publication of the Radiological Society of North America, Inc Jan 1, 2017
Deep learning is a class of machine learning methods that are gaining success and attracting interest in many domains, including computer vision, speech recognition, natural language processing, and playing games. Deep learning methods produce a mapp...
Humans Neural Networks, Computer Machine Learning Image Processing, Computer-Assisted Algorithms Radiology Learning Radiology Information Systems
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Introducing ZORA to Children with Severe Physical Disabilities.

Studies in health technology and informatics Jan 1, 2017
The aim of the present study was to explore the potential of a ZORA-robot based intervention in rehabilitation and special education for children with (severe) physical disabilities from the professionals perspective. The qualitative results of this ...
Children with Disabilities Robotics Interpersonal Relations Communication Child Humans Learning
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Imitative and Direct Learning as Interacting Factors in Life History Evolution.

Artificial life Jan 1, 2017
The idea that lifetime learning can have a significant effect on life history evolution has recently been explored using a series of artificial life simulations. These involved populations of competing individuals evolving by natural selection to lea...
Artificial Intelligence Life History Traits Biological Evolution Learning Imitative Behavior Robotics
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Cultural Transmission and Evolution of Melodic Structures in Multi-generational Signaling Games.

Artificial life Jan 1, 2017
It has been proposed that languages evolve by adapting to the perceptual and cognitive constraints of the human brain, developing, in the course of cultural transmission, structural regularities that maximize or optimize learnability and ease of proc...
Game Theory Cultural Evolution Humans Learning Artificial Intelligence Music
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Muscle co-contraction patterns in robot-mediated force field learning to guide specific muscle group training.

NeuroRehabilitation Jan 1, 2017
BACKGROUND: Muscle co-contraction is a strategy of increasing movement accuracy and stability employed in dealing with force perturbation of movement. It is often seen in neuropathological populations. The direction of movement influences the pattern...
Muscle, Skeletal Robotics Biomechanical Phenomena Male Movement Adaptation, Physiological Electromyography Muscle Contraction Humans Female Adult Learning
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