AIMC Topic: Animals

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Artificial intelligence in veterinary diagnostic imaging: Perspectives and limitations.

Research in veterinary science
The field of veterinary diagnostic imaging is undergoing significant transformation with the integration of artificial intelligence (AI) tools. This manuscript provides an overview of the current state and future prospects of AI in veterinary diagnos...

Machine-learning based detection of marine mammal vocalizations in snapping-shrimp dominated ambient noise.

Marine environmental research
Passive acoustics is an effective method for monitoring marine mammals, facilitating both detection and population estimation. In warm tropical waters, this technique encounters challenges due to the high persistent level of ambient impulsive noise o...

SIMS: A deep-learning label transfer tool for single-cell RNA sequencing analysis.

Cell genomics
Cell atlases serve as vital references for automating cell labeling in new samples, yet existing classification algorithms struggle with accuracy. Here we introduce SIMS (scalable, interpretable machine learning for single cell), a low-code data-effi...

How well do models of visual cortex generalize to out of distribution samples?

PLoS computational biology
Unit activity in particular deep neural networks (DNNs) are remarkably similar to the neuronal population responses to static images along the primate ventral visual cortex. Linear combinations of DNN unit activities are widely used to build predicti...

Estimating receptive fields of simple and complex cells in early visual cortex: A convolutional neural network model with parameterized rectification.

PLoS computational biology
Neurons in the primary visual cortex respond selectively to simple features of visual stimuli, such as orientation and spatial frequency. Simple cells, which have phase-sensitive responses, can be modeled by a single receptive field filter in a linea...

Higher heating value estimation of wastes and fuels from ultimate and proximate analysis by using artificial neural networks.

Waste management (New York, N.Y.)
Higher heating value (HHV) is one of the most important parameters in determining the quality of the fuels. In this study, comparatively large datasets of ultimate and proximate analysis are constructed to be used in HHV estimation of several classes...

Detection of milk adulteration using coffee ring effect and convolutional neural network.

Food additives & contaminants. Part A, Chemistry, analysis, control, exposure & risk assessment
A low-cost and effective method is reported to identify water and synthetic milk adulteration of cow's milk using coffee ring patterns. The cow's milk samples were diluted with tap water (TW), distilled water (DW) and mineral water (MW) and drop cast...

Enhancing liver fibrosis diagnosis and treatment assessment: a novel biomechanical markers-based machine learning approach.

Physics in medicine and biology
Accurate diagnosis and treatment assessment of liver fibrosis face significant challenges, including inherent limitations in current techniques like sampling errors and inter-observer variability. Addressing this, our study introduces a novel machine...

Mapping African Swine Fever and Highly Pathogenic Avian Influenza Outbreaks along the Demilitarized Zone in the Korean Peninsula.

Transboundary and emerging diseases
The Korean Demilitarized Zone (DMZ) is one of the world's most preserved habitats for wild animals and migratory birds. The area also plays a major role in the spread of infectious animal diseases, in particular, African swine fever (ASF) and highly ...

Machine learning modeling to predict causes of infectious abortions and perinatal mortalities in cattle.

Theriogenology
A plethora of infectious and non-infectious causes of bovine abortions and perinatal mortalities (APM) have been reported in literature. However, due to financial limitations or a potential zoonotic impact, many laboratories only offer a standard ana...