AI Medical Compendium Topic

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Two Computational Approaches to Visual Analogy: Task-Specific Models Versus Domain-General Mapping.

Cognitive science
Advances in artificial intelligence have raised a basic question about human intelligence: Is human reasoning best emulated by applying task-specific knowledge acquired from a wealth of prior experience, or is it based on the domain-general manipulat...

Revisiting Transfer Learning Method for Tuberculosis Diagnosis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Transfer learning (TL) has been proven to be a good strategy for solving domain-specific problems in many deep learning (DL) applications. Typically, in TL, a pre-trained DL model is used as a feature extractor and the extracted features are then fed...

Dual-process system based on mixed semantic fusion for Chinese medical knowledge-based question answering.

Mathematical biosciences and engineering : MBE
Chinese medical knowledge-based question answering (cMed-KBQA) is a vital component of the intelligence question-answering assignment. Its purpose is to enable the model to comprehend questions and then deduce the proper answer from the knowledge bas...

An approach to solving optimal control problems of nonlinear systems by introducing detail-reward mechanism in deep reinforcement learning.

Mathematical biosciences and engineering : MBE
In recent years, dynamic programming and reinforcement learning theory have been widely used to solve the nonlinear control system (NCS). Among them, many achievements have been made in the construction of network model and system stability analysis,...

Evolving Multimodal Robot Behavior via Many Stepping Stones with the Combinatorial Multiobjective Evolutionary Algorithm.

Evolutionary computation
An important challenge in reinforcement learning is to solve multimodal problems, where agents have to act in qualitatively different ways depending on the circumstances. Because multimodal problems are often too difficult to solve directly, it is of...

Understanding the Computational Demands Underlying Visual Reasoning.

Neural computation
Visual understanding requires comprehending complex visual relations between objects within a scene. Here, we seek to characterize the computational demands for abstract visual reasoning. We do this by systematically assessing the ability of modern d...

Human-in-the-Loop Low-Shot Learning.

IEEE transactions on neural networks and learning systems
We consider a human-in-the-loop scenario in the context of low-shot learning. Our approach was inspired by the fact that the viability of samples in novel categories cannot be sufficiently reflected by those limited observations. Some heterogeneous s...

A Neural Network Based on the Metric Projector for Solving SOCCVI Problem.

IEEE transactions on neural networks and learning systems
We propose an efficient neural network for solving the second-order cone constrained variational inequality (SOCCVI). The network is constructed using the Karush-Kuhn-Tucker (KKT) conditions of the variational inequality (VI), which is used to recast...

A Two-Timescale Duplex Neurodynamic Approach to Mixed-Integer Optimization.

IEEE transactions on neural networks and learning systems
This article presents a two-timescale duplex neurodynamic approach to mixed-integer optimization, based on a biconvex optimization problem reformulation with additional bilinear equality or inequality constraints. The proposed approach employs two re...