AIMC Topic: Animals

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Branching principles of animal and plant networks identified by combining extensive data, machine learning and modelling.

Journal of the Royal Society, Interface
Branching in vascular networks and in overall organismic form is one of the most common and ancient features of multicellular plants, fungi and animals. By combining machine-learning techniques with new theory that relates vascular form to metabolic ...

Robotic-Assisted Peripheral Nerve Surgery: A Systematic Review.

Journal of reconstructive microsurgery
BACKGROUND:  Robotic-assisted techniques are a tremendous revolution in modern surgery, and the advantages and indications were well discussed in different specialties. However, the use of robotic technique in plastic and reconstructive surgery is st...

Screening For Bone Marrow Cellularity Changes in Cynomolgus Macaques in Toxicology Safety Studies Using Artificial Intelligence Models.

Toxicologic pathology
Many compounds affect the cellularity of hematolymphoid organs including bone marrow. Toxicologic pathologists are tasked with their evaluation as part of safety studies. An artificial intelligence (AI) tool could provide diagnostic support for the p...

Robotic Assessment of Upper Limb Function in a Nonhuman Primate Model of Chronic Stroke.

Translational stroke research
Stroke is a leading cause of death and disability worldwide and survivors are frequently left with long-term disabilities that diminish their autonomy and result in the need for chronic care. There is an urgent need for the development of therapies t...

An efficient method for building a database of diatom populations for drowning site inference using a deep learning algorithm.

International journal of legal medicine
Seasonal or monthly databases of the diatom populations in specific bodies of water are needed to infer the drowning site of a drowned body. However, existing diatom testing methods are laborious, time-consuming, and costly and usually require specif...

Ear-Bot: Locust Ear-on-a-Chip Bio-Hybrid Platform.

Sensors (Basel, Switzerland)
During hundreds of millions of years of evolution, insects have evolved some of the most efficient and robust sensing organs, often far more sensitive than their man-made equivalents. In this study, we demonstrate a hybrid bio-technological approach,...

A comparative analysis of deep learning architectures on high variation malaria parasite classification dataset.

Tissue & cell
Malaria, one of the leading causes of death in underdeveloped countries, is primarily diagnosed using microscopy. Computer-aided diagnosis of malaria is a challenging task owing to the fine-grained variability in the appearance of some uninfected and...

Deep Learning in Toxicologic Pathology: A New Approach to Evaluate Rodent Retinal Atrophy.

Toxicologic pathology
Quantification of retinal atrophy, caused by therapeutics and/or light, by manual measurement of retinal layers is labor intensive and time-consuming. In this study, we explored the role of deep learning (DL) in automating the assessment of retinal a...