AIMC Topic: Animals

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Design and development of a robotic predator as a stimulus in conditioned place aversion for the study of the effect of ethanol and citalopram in zebrafish.

Behavioural brain research
Zebrafish are becoming a species of choice in psychopharmacology, laying a promising path to refined pharmacological manipulations and high-throughput behavioral phenotyping. The field of robotics has the potential to accelerate progress along this p...

Unsupervised machine learning for exploratory data analysis in imaging mass spectrometry.

Mass spectrometry reviews
Imaging mass spectrometry (IMS) is a rapidly advancing molecular imaging modality that can map the spatial distribution of molecules with high chemical specificity. IMS does not require prior tagging of molecular targets and is able to measure a larg...

A machine learning approach for the identification of population-informative markers from high-throughput genotyping data: application to several pig breeds.

Animal : an international journal of animal bioscience
Single nucleotide polymorphisms (SNPs) able to describe population differences can be used for important applications in livestock, including breed assignment of individual animals, authentication of mono-breed products and parentage verification amo...

The quantization error in a Self-Organizing Map as a contrast and colour specific indicator of single-pixel change in large random patterns.

Neural networks : the official journal of the International Neural Network Society
The quantization error in a fixed-size Self-Organizing Map (SOM) with unsupervised winner-take-all learning has previously been used successfully to detect, in minimal computation time, highly meaningful changes across images in medical time series a...

Study on miR-384-5p activates TGF-β signaling pathway to promote neuronal damage in abutment nucleus of rats based on deep learning.

Artificial intelligence in medicine
BACKGROUND: Any ailment in our organs can be visualized by using different modality signals and images. Hospitals are encountering a massive influx of large multimodality patient data to be analysed accurately and with context understanding. The deep...

Extended-wavelength diffuse reflectance spectroscopy with a machine-learning method for in vivo tissue classification.

PloS one
OBJECTIVES: An extended-wavelength diffuse reflectance spectroscopy (EWDRS) technique was evaluated for its ability to differentiate between and classify different skin and tissue types in an in vivo pig model.

Visual Correspondences for Unsupervised Domain Adaptation on Electron Microscopy Images.

IEEE transactions on medical imaging
We present an Unsupervised Domain Adaptation strategy to compensate for domain shifts on Electron Microscopy volumes. Our method aggregates visual correspondences-motifs that are visually similar across different acquisitions-to infer changes on the ...

Hybrid Artificial Bee Colony Algorithm for a Parallel Batching Distributed Flow-Shop Problem With Deteriorating Jobs.

IEEE transactions on cybernetics
In this article, we propose a hybrid artificial bee colony (ABC) algorithm to solve a parallel batching distributed flow-shop problem (DFSP) with deteriorating jobs. In the considered problem, there are two stages as follows: 1) in the first stage, a...

Deep learning-based MR-to-CT synthesis: The influence of varying gradient echo-based MR images as input channels.

Magnetic resonance in medicine
PURPOSE: To study the influence of gradient echo-based contrasts as input channels to a 3D patch-based neural network trained for synthetic CT (sCT) generation in canine and human populations.

Ovarian Toxicity Assessment in Histopathological Images Using Deep Learning.

Toxicologic pathology
As ovarian toxicity is often a safety concern for cancer therapeutics, identification of ovarian pathology is important in early stages of preclinical drug development, particularly when the intended patient population include women of child-bearing ...