AIMC Topic: Fishes

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Enhanced detection of Argulus and epizootic ulcerative syndrome in fish aquaculture through an improved deep learning model.

Journal of aquatic animal health
OBJECTIVE: Fish disease in aquaculture is a major risk to food safety. The identification of infected fish and disease categories present in fish farms remains difficult to determine at an early stage. Detecting infected fish in time is an essential ...

Prediction of bioconcentration factors (BCFs) and bioaccumulation factors (BAFs) for per- and polyfluoroalkyl substances (PFASs) using Read-Across and q-RASPR.

The Science of the total environment
Per- and polyfluoroalkyl substances (PFASs) contamination poses an environmental concern due to their ability to bioaccumulate in aquatic species and adversely impact human health. Experimental bioconcentration factor (log BCF) data of freshwater fis...

Machine Learning-Assisted Tissue-Residue-Based Risk Assessment for Protecting Threatened and Endangered Fishes in the Yangtze River Basin.

Environmental science & technology
Assessing pollutant risks to threatened and endangered (T&E) species is crucial for their conservation. However, traditional risk assessment methods for bioaccumulative pollutants to T&E fishes is challenging due to uncertainties in exposure-based to...

Unique bioaccumulation and biosynthesis of arsenobetaine in marine fish.

Aquatic toxicology (Amsterdam, Netherlands)
Arsenic (As) contamination represents a significant global concern, particularly prevalent in regions such as China, South Asia, and Southeast Asia. Arsenic permeates the food chain, posing potential hazards to ecosystems and human health. Studies ha...

Harnessing the fish gut microbiome and immune system to enhance disease resistance in aquaculture.

Fish & shellfish immunology
The increasing global reliance on aquaculture is challenged by disease outbreaks, exacerbated by antibiotic resistance, and environmental stressors. Traditional strategies, such as antibiotic treatments and chemical interventions, are becoming less e...

Predictive modeling and interpretability analysis of bioconcentration factors for organic chemicals in fish using machine learning.

Environmental pollution (Barking, Essex : 1987)
Chemicals are misused and released into the environment, causing adverse effects on people and ecosystems. Assessing the potential environmental risks of these chemicals before their use is crucial. The bioconcentration factor (BCF) is a key paramete...

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...

Quantifying Area Back Scatter of Marine Organisms in the Arctic Ocean by Machine Learning-Based Post-Processing of Volume Back Scatter.

Sensors (Basel, Switzerland)
As the sea ice reduces in both extent and thickness and the Arctic Ocean opens, there is substantial interest in mapping the marine ecosystem in this remote and until now largely inaccessible ocean. We used the during surveys in the Central Arctic O...

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...

Application and effectiveness of artificial intelligence for the border management of imported frozen fish in Taiwan.

Journal of food and drug analysis
In Taiwan, the number of applications for inspecting imported food has grown annually and noncompliant products must be accurately detected in these border sampling inspections. Previously, border management has used an automated border inspection sy...