AI Medical Compendium Topic:
Databases, Factual

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Automatic construction of molecular similarity networks for visual graph mining in chemical space of bioactive peptides: an unsupervised learning approach.

Scientific reports
The increasing interest in bioactive peptides with therapeutic potentials has been reflected in a large variety of biological databases published over the last years. However, the knowledge discovery process from these heterogeneous data sources is a...

Self-evoluting framework of deep convolutional neural network for multilocus protein subcellular localization.

Medical & biological engineering & computing
In the present paper, deep convolutional neural network (DCNN) is applied to multilocus protein subcellular localization as it is more suitable for multi-class classification. There are two main problems with this application. First, the appropriate ...

Predicting human health from biofluid-based metabolomics using machine learning.

Scientific reports
Biofluid-based metabolomics has the potential to provide highly accurate, minimally invasive diagnostics. Metabolomics studies using mass spectrometry typically reduce the high-dimensional data to only a small number of statistically significant feat...

Predicting adverse drug reactions of two-drug combinations using structural and transcriptomic drug representations to train an artificial neural network.

Chemical biology & drug design
Adverse drug reactions (ADRs) are pharmacological events triggered by drug interactions with various sources of origin including drug-drug interactions. While there are many computational studies that explore models to predict ADRs originating from s...

Imaging Database Preparation for Machine Learning.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes

CoLe-CNN: Context-learning convolutional neural network with adaptive loss function for lung nodule segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: An accurate segmentation of lung nodules in computed tomography images is a crucial step for the physical characterization of the tumour. Being often completely manually accomplished, nodule segmentation turns to be a tediou...

Finding, visualizing, and quantifying latent structure across diverse animal vocal repertoires.

PLoS computational biology
Animals produce vocalizations that range in complexity from a single repeated call to hundreds of unique vocal elements patterned in sequences unfolding over hours. Characterizing complex vocalizations can require considerable effort and a deep intui...

The parable of arable land: Characterizing large scale land acquisitions through network analysis.

PloS one
Land is a scarce resource and its depletion is related to a combination of demographic and economic factors. Hence, the changes in dietary habits and increase in world population that upturn the food demand, are intertwined with a context of increasi...

Unsupervised learning for large-scale corneal topography clustering.

Scientific reports
Machine learning algorithms have recently shown their precision and potential in many different use cases and fields of medicine. Most of the algorithms used are supervised and need a large quantity of labeled data to achieve high accuracy. Also, mos...