AIMC Topic: Deep Learning

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Cross-type biomedical named entity recognition with deep multi-task learning.

Bioinformatics (Oxford, England)
MOTIVATION: State-of-the-art biomedical named entity recognition (BioNER) systems often require handcrafted features specific to each entity type, such as genes, chemicals and diseases. Although recent studies explored using neural network models for...

Differentiating post-cancer from healthy tongue muscle coordination patterns during speech using deep learning.

The Journal of the Acoustical Society of America
The ability to differentiate post-cancer from healthy tongue muscle coordination patterns is necessary for the advancement of speech motor control theories and for the development of therapeutic and rehabilitative strategies. A deep learning approach...

A Deep Learning-Based Decision Support Tool for Precision Risk Assessment of Breast Cancer.

JCO clinical cancer informatics
PURPOSE: The Breast Imaging Reporting and Data System (BI-RADS) lexicon was developed to standardize mammographic reporting to assess cancer risk and facilitate the decision to biopsy. Because of substantial interobserver variability in the applicati...

A photometric stereo-based 3D imaging system using computer vision and deep learning for tracking plant growth.

GigaScience
BACKGROUND: Tracking and predicting the growth performance of plants in different environments is critical for predicting the impact of global climate change. Automated approaches for image capture and analysis have allowed for substantial increases ...

Opportunities and challenges using artificial intelligence in ADME/Tox.

Nature materials
A recent conference organized a panel of scientists representing small and big pharma companies, who work at the interface of machine learning (ML) and absorption, distribution, metabolism, excretion, and toxicology (ADME/Tox). With the recent rebirt...