AIMC Topic: Animals

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Forestwalk: A Machine Learning Workflow Brings New Insights Into Posture and Balance in Rodent Beam Walking.

The European journal of neuroscience
The beam walk is widely used to study coordination and balance in rodents. While the task has ethological validity, the main endpoints of "foot slip counts" and "time to cross" are prone to human-rater variability and offer limited sensitivity and sp...

Enhancing single-cell classification accuracy using image conversion and deep learning.

Yi chuan = Hereditas
Single-cell transcriptome sequencing (scRNA-seq) is widely used in the fields of animal and plant developmental biology and important trait analysis by obtaining single-cell transcript abundance data in high throughput, which can deeply reveal cell t...

Rapid detection of fish calls within diverse coral reef soundscapes using a convolutional neural networka).

The Journal of the Acoustical Society of America
The quantity of passive acoustic data collected in marine environments is rapidly expanding; however, the software developments required to meaningfully process large volumes of soundscape data have lagged behind. A significant bottleneck in the anal...

A Pilot Study on Using an Artificial Intelligence Algorithm to Identify Urolith Composition through Abdominal Radiographs in the Dog.

Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association
In small animal practice, patients often present with urinary lithiasis, and prediction of urolith composition is essential to determine the appropriate treatment. Through abdominal radiographs, the composition of mineral radiopaque uroliths can be d...

Exploring the dynamics of Lotka-Volterra systems: Efficiency, extinction order, and predictive machine learning.

Chaos (Woodbury, N.Y.)
For years, a main focus of ecological research has been to better understand the complex dynamical interactions between species that comprise food webs. Using the connectance properties of a widely explored synthetic food web called the cascade model...

Quantifying Facial Gestures Using Deep Learning in a New World Monkey.

American journal of primatology
Facial gestures are a crucial component of primate multimodal communication. However, current methodologies for extracting facial data from video recordings are labor-intensive and prone to human subjectivity. Although automatic tools for this task a...

Interpretable Artificial Intelligence for Analysing Changes in Gases in the Uterine Environment of Cows According to Physiological Structures in the Ovary.

Veterinary medicine and science
The objective of the present study was to examine the relationship between the gases in a cow's uterine environment and its ovarian physiological structures using the sunflower optimisation algorithm (SFOA) deployed in a device called Metrisör, devel...

A Veterinary DICOM-Based Deep Learning Denoising Algorithm Can Improve Subjective and Objective Brain MRI Image Quality.

Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association
In this analytical cross-sectional method comparison study, we evaluated brain MR images in 30 dogs and cats with and without using a DICOM-based deep-learning (DL) denoising algorithm developed specifically for veterinary patients. Quantitative comp...

IAMPDB: A Knowledgebase of Manually Curated Insects-Derived Antimicrobial Peptides.

Journal of peptide science : an official publication of the European Peptide Society
Insects, a majority of animal species, rely on innate immunity and antimicrobial peptides (AMPs), which are a part of their innate immunity, to combat diverse parasites and pathogens. These peptides have applications ranging from agriculture to antim...

stAI: a deep learning-based model for missing gene imputation and cell-type annotation of spatial transcriptomics.

Nucleic acids research
Spatial transcriptomics technology has revolutionized our understanding of cellular systems by capturing RNA transcript levels in their original spatial context. Single-cell spatial transcriptomics (scST) offers single-cell resolution expression leve...