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Biomedical Research

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Voting-based integration algorithm improves causal network learning from interventional and observational data: An application to cell signaling network inference.

PloS one
In order to increase statistical power for learning a causal network, data are often pooled from multiple observational and interventional experiments. However, if the direct effects of interventions are uncertain, multi-experiment data pooling can r...

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,...

Promises and pitfalls of deep neural networks in neuroimaging-based psychiatric research.

Experimental neurology
By promising more accurate diagnostics and individual treatment recommendations, deep neural networks and in particular convolutional neural networks have advanced to a powerful tool in medical imaging. Here, we first give an introduction into method...

SpiNet - A FrameNet-like Schema for Automatic Information Extraction about Spine from Scientific Papers.

AMIA ... Annual Symposium proceedings. AMIA Symposium
New medical research concerning the spine and its diseases are incrementally made available through biomedical literature repositories. Several Natural Language Processing (NLP) tasks, like Semantic Role Labelling (SRL) and Information Extraction (IE...

Artificial Intelligence in Nutrients Science Research: A Review.

Nutrients
Artificial intelligence (AI) as a branch of computer science, the purpose of which is to imitate thought processes, learning abilities and knowledge management, finds more and more applications in experimental and clinical medicine. In recent decades...

Application of Artificial Intelligence for Medical Research.

Biomolecules
The Human Genome Project, completed in 2003 by an international consortium, is considered one of the most important achievements for mankind in the 21st century [...].

ARDD 2020: from aging mechanisms to interventions.

Aging
Aging is emerging as a druggable target with growing interest from academia, industry and investors. New technologies such as artificial intelligence and advanced screening techniques, as well as a strong influence from the industry sector may lead t...

How wide is the application of genetic big data in biomedicine.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
In the era of big data, massive genetic data, as a new industry, has quickly swept almost all industries, especially the pharmaceutical industry. As countries around the world start to build their own gene banks, scientists study the data to explore ...

LSTM-Based End-to-End Framework for Biomedical Event Extraction.

IEEE/ACM transactions on computational biology and bioinformatics
Biomedical event extraction plays an important role in the extraction of biological information from large-scale scientific publications. However, most state-of-the-art systems separate this task into several steps, which leads to cascading errors. I...