AIMC Topic: Animals

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A Weakly Supervised Deep Learning Framework for Whole Slide Classification to Facilitate Digital Pathology in Animal Study.

Chemical research in toxicology
The pathology of animal studies is crucial for toxicity evaluations and regulatory assessments, but the manual examination of slides by pathologists remains time-consuming and requires extensive training. One inherent challenge in this process is the...

Species-specific wiring of cortical circuits for small-world networks in the primary visual cortex.

PLoS computational biology
Long-range horizontal connections (LRCs) are conspicuous anatomical structures in the primary visual cortex (V1) of mammals, yet their detailed functions in relation to visual processing are not fully understood. Here, we show that LRCs are key compo...

Soil Moisture and Heat Level Prediction for Plant Health Monitoring Using Deep Learning with Gannet Namib Beetle Optimization in IoT.

Applied biochemistry and biotechnology
Plant health monitoring is crucial in ensuring a constant food supply to satisfy the growing demand for food. Hence, it is essential to monitor plant health to maximize the yield and minimize the risk of various diseases. Soil moisture and temperatur...

Comparison of the data mining and machine learning algorithms for predicting the final body weight for Romane sheep breed.

PloS one
The current study aimed to predict final body weight (weight of fourth months of age to select the future reproducers) by using birth weight, birth type, sex, suckling weight, age at suckling weight, weaning weight, age at weaning weight, and age of ...

Artificial intelligence-assisted repurposing of lubiprostone alleviates tubulointerstitial fibrosis.

Translational research : the journal of laboratory and clinical medicine
Tubulointerstitial fibrosis (TIF) is the most prominent cause which leads to chronic kidney disease (CKD) and end-stage renal failure. Despite extensive research, there have been many clinical trial failures, and there is currently no effective treat...

Identifying the active ingredients of carbonized Typhae Pollen by spectrum-effect relationship combined with MBPLS, PLS, and SVM algorithms.

Journal of pharmaceutical and biomedical analysis
Typhae Pollen (TP) and its carbonized product (carbonized Typhae Pollen, CTP), as cut-and-dried herbal drugs, have been widely used in the form of slices in clinical settings. However, the two drugs exhibit a great difference in terms of their clinic...

A knowledge-integrated deep learning framework for cellular image analysis in parasite microbiology.

STAR protocols
Cellular image analysis is an important method for microbiologists to identify and study microbes. Here, we present a knowledge-integrated deep learning framework for cellular image analysis, using three tasks as examples: classification, detection, ...

Machine learning prediction and classification of behavioral selection in a canine olfactory detection program.

Scientific reports
There is growing interest in canine behavioral research specifically for working dogs. Here we take advantage of a dataset of a Transportation Safety Administration olfactory detection cohort of 628 Labrador Retrievers to perform Machine Learning (ML...

deepGBLUP: joint deep learning networks and GBLUP framework for accurate genomic prediction of complex traits in Korean native cattle.

Genetics, selection, evolution : GSE
BACKGROUND: Genomic prediction has become widespread as a valuable tool to estimate genetic merit in animal and plant breeding. Here we develop a novel genomic prediction algorithm, called deepGBLUP, which integrates deep learning networks and a geno...

Automated diagnosis of 7 canine skin tumors using machine learning on H&E-stained whole slide images.

Veterinary pathology
Microscopic evaluation of hematoxylin and eosin-stained slides is still the diagnostic gold standard for a variety of diseases, including neoplasms. Nevertheless, intra- and interrater variability are well documented among pathologists. So far, compu...