AIMC Topic: Animals

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Deploying deep learning to estimate the abundance of marine debris from video footage.

Marine pollution bulletin
The insatiable desire of society for plastic goods has led to synthetic materials becoming omnipresent in the marine environment. In attempting to address the problem of plastic pollution, we propose an image classifier based on the YOLOv5 deep learn...

Predicting Total Drug Clearance and Volumes of Distribution Using the Machine Learning-Mediated Multimodal Method through the Imputation of Various Nonclinical Data.

Journal of chemical information and modeling
Pharmacokinetic research plays an important role in the development of new drugs. Accurate predictions of human pharmacokinetic parameters are essential for the success of clinical trials. Clearance (CL) and volume of distribution (Vd) are important ...

DeepBSA: A deep-learning algorithm improves bulked segregant analysis for dissecting complex traits.

Molecular plant
Bulked segregant analysis (BSA) is a rapid, cost-effective method for mapping mutations and quantitative trait loci (QTLs) in animals and plants based on high-throughput sequencing. However, the algorithms currently used for BSA have not been systema...

Study on image data cleaning method of early esophageal cancer based on VGG_NIN neural network.

Scientific reports
In order to clean the mislabeled images in the esophageal endoscopy image data set, we designed a new neural network VGG_NIN. Based on the new neural network structure, we developed a method to clean the mislabeled images in the esophageal endoscopy ...

An annotated image dataset of medically and forensically important flies for deep learning model training.

Scientific data
Conventional methods to study insect taxonomy especially forensic and medical dipterous flies are often tedious, time-consuming, labor-intensive, and expensive. An automated recognition system with image processing and computer vision provides an exc...

Fully automated mouse echocardiography analysis using deep convolutional neural networks.

American journal of physiology. Heart and circulatory physiology
Echocardiography (echo) is a translationally relevant ultrasound imaging modality widely used to assess cardiac structure and function in preclinical models of heart failure (HF) during research and drug development. Although echo is a very valuable ...

Automated optimization of multilevel models of collective behaviour: application to mixed society of animals and robots.

Bioinspiration & biomimetics
Animal societies exhibit complex dynamics that require multi-level descriptions. They are difficult to model, as they encompass information at different levels of description, such as individual physiology, individual behaviour, group behaviour and f...

Development of a spontaneous pain indicator based on brain cellular calcium using deep learning.

Experimental & molecular medicine
Chronic pain remains an intractable condition in millions of patients worldwide. Spontaneous ongoing pain is a major clinical problem of chronic pain and is extremely challenging to diagnose and treat compared to stimulus-evoked pain. Although extens...

A deep learning method for predicting molecular properties and compound-protein interactions.

Journal of molecular graphics & modelling
Predicting molecular properties and compound-protein interactions (CPIs) are two important areas of drug design and discovery. They are also an essential way to discover lead compounds in virtual screening. Recently, in silico methods based on deep l...

Feasibility of Laser Lithotripsy for Midsize Stones Using Robotic Retrograde Intrarenal Surgery System easyUretero in a Porcine Model.

Journal of endourology
To test the safety and feasibility of laser lithotripsy for midsize renal stones using a newly developed robotic retrograde intrarenal surgery (RIRS) system (easyUretero) in a porcine model. Three urologic surgeons representing three different RIRS...