AI Medical Compendium Topic

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Livestock

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A Systematic Review and Meta-Analysis of the Efficacy of Biosecurity in Disease Prevention and Control in Livestock Farms in Africa.

Transboundary and emerging diseases
In Africa, livestock production plays a crucial role for sustainable food security and economic growth. However, the development of this sector has been delayed by livestock diseases, one of the main constraints, which can cause important production ...

Unveiling livestock trade trends: A beginner's guide to generative AI-powered visualization.

Research in veterinary science
This tutorial, rooted in the context of livestock research, is designed to assist novice or non-programmers in visualizing trends in livestock exports between the US and Japan using Python and generative AI systems such as Microsoft's Copilot and Goo...

Ontologies related to livestock for the Global Burden of Animal Diseases programme: a review.

Revue scientifique et technique (International Office of Epizootics)
The Global Burden of Animal Diseases (GBADs) programme aims to assess the impact of animal health on agricultural animals, livestock production systems and associated communities worldwide. As part of the objectives of GBADs'Animal Health Ontology th...

Applications of Artificial Intelligence for Heat Stress Management in Ruminant Livestock.

Sensors (Basel, Switzerland)
Heat stress impacts ruminant livestock production on varied levels in this alarming climate breakdown scenario. The drastic effects of the global climate change-associated heat stress in ruminant livestock demands constructive evaluation of animal pe...

Machine Learning-Aided Ultra-Low-Density Single Nucleotide Polymorphism Panel Helps to Identify the Tharparkar Cattle Breed: Lessons for Digital Transformation in Livestock Genomics.

Omics : a journal of integrative biology
Cattle breed identification is crucial for livestock research and sustainable food systems, and advances in genomics and artificial intelligence present new opportunities to address these challenges. This study investigates the identification of the ...

Progress on deep learning in genomics.

Yi chuan = Hereditas
With the rapid growth of data driven by high-throughput sequencing technologies, genomics has entered an era characterized by big data, which presents significant challenges for traditional bioinformatics methods in handling complex data patterns. At...

Design optimization of bimetal-modified biochar for enhanced phosphate removal performance in livestock wastewater using machine learning.

Bioresource technology
Mg-modified biochar shows high adsorption performance under weakly acidic and neutral water conditions. However, its phosphate removal efficiency markedly decreases in naturally alkaline wastewater, such as that released in livestock farming (anaerob...

Interval price prediction of livestock product based on fuzzy mathematics and improved LSTM.

PloS one
Livestock product prices serve as a barometer and bellwether for the agricultural market. However, traditional point prediction techniques focus mainly on tracking or fitting, resulting in limited information and challenges in evaluating the uncertai...

Beyond the hype: using AI, big data, wearable devices, and the internet of things for high-throughput livestock phenotyping.

Briefings in functional genomics
Phenotyping of animals is a routine task in agriculture which can provide large datasets for the functional annotation of genomes. Using the livestock farming sector to study complex traits enables genetics researchers to fully benefit from the digit...

A machine learning multimodal profiling of Per- and Polyfluoroalkyls (PFAS) distribution across animal species organs via clustering and dimensionality reduction techniques.

Food research international (Ottawa, Ont.)
Per- and polyfluoroalkyl substances (PFAS) contamination in aquatic and terrestrial organisms poses significant environmental and health risks. This study quantified 15 PFAS compounds across various tissues (liver, kidney, gill, muscle, skin, lung, b...