AIMC Topic: Animals

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Deep Convolutional and Recurrent Neural Networks for Cell Motility Discrimination and Prediction.

IEEE/ACM transactions on computational biology and bioinformatics
Cells in culture display diverse motility behaviors that may reflect differences in cell state and function, providing motivation to discriminate between different motility behaviors. Current methods to do so rely upon manual feature engineering. How...

Assessing the potential for deep learning and computer vision to identify bumble bee species from images.

Scientific reports
Pollinators are undergoing a global decline. Although vital to pollinator conservation and ecological research, species-level identification is expensive, time consuming, and requires specialized taxonomic training. However, deep learning and compute...

Deep learning in forensic gunshot wound interpretation-a proof-of-concept study.

International journal of legal medicine
While the applications of deep learning are considered revolutionary within several medical specialties, forensic applications have been scarce despite the visual nature of the field. For example, a forensic pathologist may benefit from deep learning...

Deep transfer learning can be used for the detection of hip joints in pelvis radiographs and the classification of their hip dysplasia status.

Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association
Reports of machine learning implementations in veterinary imaging are infrequent but changes in machine learning architecture and access to increased computing power will likely prompt increased interest. This diagnostic accuracy study describes a pa...

Neurovascular multiparametric MRI defines epileptogenic and seizure propagation regions in experimental mesiotemporal lobe epilepsy.

Epilepsia
OBJECTIVE: Improving the identification of the epileptogenic zone and associated seizure-spreading regions represents a significant challenge. Innovative brain-imaging modalities tracking neurovascular dynamics during seizures may provide new disease...

Deep Transfer Learning Approach for Automatic Recognition of Drug Toxicity and Inhibition of SARS-CoV-2.

Viruses
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes COVID-19 and is responsible for the ongoing pandemic. Screening of potential antiviral drugs against SARS-CoV-2 depend on in vitro experiments, which are based on the quantification ...

Artificial Intelligence & Tissue Biomarkers: Advantages, Risks and Perspectives for Pathology.

Cells
Tissue Biomarkers are information written in the tissue and used in Pathology to recognize specific subsets of patients with diagnostic, prognostic or predictive purposes, thus representing the key elements of Personalized Medicine. The advent of Art...

Effects of root chord movement on thrust generation of oscillatory pectoral fins.

Bioinspiration & biomimetics
Fin kinematics is the key to thrust generation of oscillatory pectoral fins of manta rays. This could be one of the main reasons that fin designs of robotic manta rays are becoming more complex to simulate the fin kinematics more closely so as to gen...

Neuron type classification in rat brain based on integrative convolutional and tree-based recurrent neural networks.

Scientific reports
The study of cellular complexity in the nervous system based on anatomy has shown more practical and objective advantages in morphology than other perspectives on molecular, physiological, and evolutionary aspects. However, morphology-based neuron ty...

Harnessing machine learning to guide phylogenetic-tree search algorithms.

Nature communications
Inferring a phylogenetic tree is a fundamental challenge in evolutionary studies. Current paradigms for phylogenetic tree reconstruction rely on performing costly likelihood optimizations. With the aim of making tree inference feasible for problems i...