AIMC Topic: Animals

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Deep learning model shows promise for detecting and grading sesamoiditis in horse radiographs.

American journal of veterinary research
OBJECTIVE: The objective of this study was to develop a robust machine-learning approach for efficient detection and grading of sesamoiditis in horses using radiographs, specifically in data-limited conditions.

Soundscapes and deep learning enable tracking biodiversity recovery in tropical forests.

Nature communications
Tropical forest recovery is fundamental to addressing the intertwined climate and biodiversity loss crises. While regenerating trees sequester carbon relatively quickly, the pace of biodiversity recovery remains contentious. Here, we use bioacoustics...

MalariaSED: a deep learning framework to decipher the regulatory contributions of noncoding variants in malaria parasites.

Genome biology
Malaria remains one of the deadliest infectious diseases. Transcriptional regulation effects of noncoding variants in this unusual genome of malaria parasites remain elusive. We developed a sequence-based, ab initio deep learning framework, MalariaSE...

Application of multiple-finding segmentation utilizing Mask R-CNN-based deep learning in a rat model of drug-induced liver injury.

Scientific reports
Drug-induced liver injury (DILI) presents significant diagnostic challenges, and recently artificial intelligence-based deep learning technology has been used to predict various hepatic findings. In this study, we trained a set of Mask R-CNN-based de...

Cow detection and tracking system utilizing multi-feature tracking algorithm.

Scientific reports
In modern cattle farm management systems, video-based monitoring has become important in analyzing the high-level behavior of cattle for monitoring their health and predicting calving for providing timely assistance. Conventionally, sensors have been...

Comparing Inertial Measurement Units to Markerless Video Analysis for Movement Symmetry in Quarter Horses.

Sensors (Basel, Switzerland)
BACKGROUND: With an increasing number of systems for quantifying lameness-related movement asymmetry, between-system comparisons under non-laboratory conditions are important for multi-centre or referral-level studies. This study compares an artifici...

U-Net based vessel segmentation for murine brains with small micro-magnetic resonance imaging reference datasets.

PloS one
Identification and quantitative segmentation of individual blood vessels in mice visualized with preclinical imaging techniques is a tedious, manual or semiautomated task that can require weeks of reviewing hundreds of levels of individual data sets....

Polygenic modelling and machine learning approaches in pharmacogenomics: Importance in downstream analysis of genome-wide association study data.

British journal of clinical pharmacology
Genome-wide association studies (GWAS) have identified genetic variations associated with adverse drug effects in pharmacogenomics (PGx) research. However, interpreting the biological implications of these associations remains a challenge. This revie...

Automatic identification and morphological comparison of bivalve and brachiopod fossils based on deep learning.

PeerJ
Fossil identification is an essential and fundamental task for conducting palaeontological research. Because the manual identification of fossils requires extensive experience and is time-consuming, automatic identification methods are proposed. Howe...