AIMC Topic: Animals

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Dose reduction and image enhancement in micro-CT using deep learning.

Medical physics
BACKGROUND: In preclinical settings, micro-computed tomography (CT) provides a powerful tool to acquire high resolution anatomical images of rodents and offers the advantage to in vivo non-invasively assess disease progression and therapy efficacy. M...

A vacuum-actuated soft robot inspired by Drosophila larvae to study kinetics of crawling behaviour.

PloS one
Peristalsis, a motion generated by the propagation of muscular contraction along the body axis, is one of the most common locomotion patterns in limbless animals. While the kinematics of peristalsis has been examined intensively, its kinetics remains...

Hybrid optimized feature selection and deep learning based COVID-19 disease prediction.

Computer methods in biomechanics and biomedical engineering
The COVID-19 virus has affected many people around the globe with several issues. Moreover, it causes a worldwide pandemic, and it makes more than one million deaths. Countries around the globe had to announce a complete lockdown when the corona viru...

The emerging role of artificial intelligence and digital twins in pre-clinical molecular imaging.

Nuclear medicine and biology
INTRODUCTION: Pre-clinical molecular imaging, particularly with mice, is an essential part of drug and radiopharmaceutical development. There remain ethical challenges to reduce, refine and replace animal imaging where possible.

An end-to-end pipeline based on open source deep learning tools for reliable analysis of complex 3D images of ovaries.

Development (Cambridge, England)
Computational analysis of bio-images by deep learning (DL) algorithms has made exceptional progress in recent years and has become much more accessible to non-specialists with the development of ready-to-use tools. The study of oogenesis mechanisms a...

DL-m6A: Identification of N6-Methyladenosine Sites in Mammals Using Deep Learning Based on Different Encoding Schemes.

IEEE/ACM transactions on computational biology and bioinformatics
N6-methyladenosine (m6A) is a common post-transcriptional alteration that plays a critical function in a variety of biological processes. Although experimental approaches for identifying m6A sites have been developed and deployed, they are currently ...

Machine learning-assisted data filtering and QSAR models for prediction of chemical acute toxicity on rat and mouse.

Journal of hazardous materials
Machine learning (ML) methods provide a new opportunity to build quantitative structure-activity relationship (QSAR) models for predicting chemicals' toxicity based on large toxicity data sets, but they are limited in insufficient model robustness du...

Tough, Recyclable, and Degradable Elastomers for Potential Biomedical Applications.

Advanced materials (Deerfield Beach, Fla.)
Elastomers have many industrial, medical and commercial applications, however, their huge demand raises an important question of how to dispose of the out-of-service elastomers. Ideal elastomers that are concurrently tough, recyclable, and degradable...

Recognition of Abnormal-Laying Hens Based on Fast Continuous Wavelet and Deep Learning Using Hyperspectral Images.

Sensors (Basel, Switzerland)
The egg production of laying hens is crucial to breeding enterprises in the laying hen breeding industry. However, there is currently no systematic or accurate method to identify low-egg-production-laying hens in commercial farms, and the majority of...

Robust and reusable self-organized locomotion of legged robots under adaptive physical and neural communications.

Frontiers in neural circuits
INTRODUCTION: Animals such as cattle can achieve versatile and elegant behaviors through automatic sensorimotor coordination. Their self-organized movements convey an impression of adaptability, robustness, and motor memory. However, the adaptive mec...