AI Medical Compendium Topic

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Predicting User Susceptibility to Phishing Based on Multidimensional Features.

Computational intelligence and neuroscience
While antiphishing techniques have evolved over the years, phishing remains one of the most threatening attacks on current network security. This is because phishing exploits one of the weakest links in a network system-people. The purpose of this re...

Configurable Graph Reasoning for Visual Relationship Detection.

IEEE transactions on neural networks and learning systems
Visual commonsense knowledge has received growing attention in the reasoning of long-tailed visual relationships biased in terms of object and relation labels. Most current methods typically collect and utilize external knowledge for visual relations...

Multipath Cross Graph Convolution for Knowledge Representation Learning.

Computational intelligence and neuroscience
In the past, most of the entity prediction methods based on embedding lacked the training of local core relationships, resulting in a deficiency in the end-to-end training. Aiming at this problem, we propose an end-to-end knowledge graph embedding re...

Responsibility, second opinions and peer-disagreement: ethical and epistemological challenges of using AI in clinical diagnostic contexts.

Journal of medical ethics
In this paper, we first classify different types of second opinions and evaluate the ethical and epistemological implications of providing those in a clinical context. Second, we discuss the issue of how artificial intelligent (AI) could replace the ...

Artificial evolution of robot bodies and control: on the interaction between evolution, learning and culture.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
We survey and reflect on how learning (in the form of individual learning and/or culture) can augment evolutionary approaches to the joint optimization of the body and control of a robot. We focus on a class of applications where the goal is to evolv...

A unified drug-target interaction prediction framework based on knowledge graph and recommendation system.

Nature communications
Prediction of drug-target interactions (DTI) plays a vital role in drug development in various areas, such as virtual screening, drug repurposing and identification of potential drug side effects. Despite extensive efforts have been invested in perfe...

Multi-view Teacher-Student Network.

Neural networks : the official journal of the International Neural Network Society
Multi-view learning aims to fully exploit the view-consistency and view-discrepancy for performance improvement. Knowledge Distillation (KD), characterized by the so-called "Teacher-Student" (T-S) learning framework, can transfer information learned ...

Augmenting BDI Agency with a Cognitive Service: Architecture and Validation in Healthcare Domain.

Journal of medical systems
Autonomous intelligent systems are starting to influence clinical practice, as ways to both readily exploit experts' knowledge when contextual conditions demand so, and harness the overwhelming amount of patient related data currently at clinicians' ...

Optimizing Deeper Spiking Neural Networks for Dynamic Vision Sensing.

Neural networks : the official journal of the International Neural Network Society
Spiking Neural Networks (SNNs) have recently emerged as a new generation of low-power deep neural networks due to sparse, asynchronous, and binary event-driven processing. Most previous deep SNN optimization methods focus on static datasets (e.g., MN...

SicknessMiner: a deep-learning-driven text-mining tool to abridge disease-disease associations.

BMC bioinformatics
BACKGROUND: Blood cancers (BCs) are responsible for over 720 K yearly deaths worldwide. Their prevalence and mortality-rate uphold the relevance of research related to BCs. Despite the availability of different resources establishing Disease-Disease ...