AI Medical Compendium Topic

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Knowledge Bases

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A new approach to medical diagnostic decision support.

Journal of biomedical informatics
Data mining is a powerful tool to reduce costs and mitigate errors in the diagnostic analysis and repair of complex engineered system, but it has yet to be applied systematically to the most complex and socially expensive system - the human body. The...

Knowledge graph embedding with shared latent semantic units.

Neural networks : the official journal of the International Neural Network Society
Knowledge graph embedding (KGE) aims to project both entities and relations into a continuous low-dimensional space. However, for a given knowledge graph (KG), only a small number of entities and relations occur many times, while the vast majority of...

Cross Knowledge-based Generative Zero-Shot Learning approach with Taxonomy Regularization.

Neural networks : the official journal of the International Neural Network Society
Although zero-shot learning (ZSL) has an inferential capability of recognizing new classes that have never been seen before, it always faces two fundamental challenges of the cross modality and cross-domain challenges. In order to alleviate these pro...

Taking a Closed-Book Examination: Decoupling KB-Based Inference by Virtual Hypothesis for Answering Real-World Questions.

Computational intelligence and neuroscience
Complex question answering in real world is a comprehensive and challenging task due to its demand for deeper question understanding and deeper inference. Information retrieval is a common solution and easy to implement, but it cannot answer question...

Information retrieval on oncology knowledge base using recursive paraphrase lattice.

Journal of biomedical informatics
For annotation in cancer genomic medicine, oncologists have to refer to various knowledge bases worldwide and retrieve all information (e.g., drugs, clinical trials, and academic papers) related to a gene variant. However, oncologists find it difficu...

Artificial intelligence in drug discovery: what is realistic, what are illusions? Part 2: a discussion of chemical and biological data.

Drug discovery today
'Artificial Intelligence' (AI) has recently had a profound impact on areas such as image and speech recognition, and this progress has already translated into practical applications. However, in the drug discovery field, such advances remains scarce,...

Knowledge Extraction of Cohort Characteristics in Research Publications.

AMIA ... Annual Symposium proceedings. AMIA Symposium
When healthcare providers review the results of a clinical trial study to understand its applicability to their practice, they typically analyze how well the characteristics of the study cohort correspond to those of the patients they see. We have pr...

A protocol for adding knowledge to Wikidata: aligning resources on human coronaviruses.

BMC biology
BACKGROUND: Pandemics, even more than other medical problems, require swift integration of knowledge. When caused by a new virus, understanding the underlying biology may help finding solutions. In a setting where there are a large number of loosely ...

Extracting and inserting knowledge into stacked denoising auto-encoders.

Neural networks : the official journal of the International Neural Network Society
Deep neural networks (DNNs) with a complex structure and multiple nonlinear processing units have achieved great successes for feature learning in image and visualization analysis. Due to interpretability of the "black box" problem in DNNs, however, ...

Unsupervised cross-domain named entity recognition using entity-aware adversarial training.

Neural networks : the official journal of the International Neural Network Society
The success of neural network based methods in named entity recognition (NER) is heavily relied on abundant manual labeled data. However, these NER methods are unavailable when the data is fully-unlabeled in a new domain. To address the problem, we p...