AIMC Topic: Animals

Clear Filters Showing 831 to 840 of 8866 articles

Artificial intelligence - based approaches based on random forest algorithm for signal analysis: Potential applications in detection of chemico - biological interactions.

Chemico-biological interactions
Random Forest (RF) is a powerful ensemble-based supervised machine learning technique that builds multiple decision trees using bootstrap aggregating and random feature selection to improve classification and regression accuracy while reducing overfi...

Multi-level evidence reveals PANK2 as a potential target of PFOA/PFOS-induced bone metabolism disruption: From network toxicology to in vitro validation.

Ecotoxicology and environmental safety
Perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) are two representative per- and polyfluoroalkyl substances (PFAS) that have attracted increasing attention due to their environmental persistence and potential health risks, while ...

AI-supported versus manual microscopy of Kato-Katz smears for diagnosis of soil-transmitted helminth infections in a primary healthcare setting.

Scientific reports
Soil-transmitted helminths primarily comprise Ascaris lumbricoides, Trichuris trichiura, and hookworms, infecting more than 600 million people globally, particularly in underserved communities. Manual microscopy of Kato-Katz thick smears is a widely ...

Neurons throughout the brain embed robust signatures of their anatomical location into spike trains.

eLife
Neurons in the brain are known to encode diverse information through their spiking activity, primarily reflecting external stimuli and internal states. However, whether individual neurons also embed information about their own anatomical location wit...

Broadscale reconnaissance of coral reefs from citizen science and deep learning.

Environmental monitoring and assessment
Coral reef managers require various forms of data. While monitoring is typically the preserve of scientists, there is an increasing need to collect larger scale, up-to-date data to prioritise limited conservation resources. Citizen science combined w...

Investigating the benefits of artificial neural networks over linear approaches to BMI decoding.

Journal of neural engineering
Brain-machine interfaces (BMI) aim to restore function to persons living with spinal cord injuries by 'decoding' neural signals into behavior. Recently, nonlinear BMI decoders have outperformed previous state-of-the-art linear decoders, but few studi...

Decomposition-reconstruction-optimization framework for hog price forecasting: Integrating STL, PCA, and BWO-optimized BiLSTM.

PloS one
This study constructs a multi-stage hybrid forecasting model using hog price time series data and its influencing factors to improve prediction accuracy. First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price serie...

Comparison of machine learning and validation methods for high-dimensional accelerometer data to detect foot lesions in dairy cattle.

PloS one
Lameness is one of the major production diseases affecting dairy cattle. It is associated with negative welfare in affected cattle, economic losses at the farm level, and adverse effects on sustainability. Prompt identification of lameness is necessa...

Drivers of fish diversity and size spectra across lagoonal habitats of the Toliara reef system (SW Madagascar).

Marine environmental research
Size-spectra and taxonomic diversity are important indicators to study the dynamics of communities and to inform conservation in aquatic ecosystems. To date, few studies aimed at modelling the distribution of reef fish diversity at small spatial scal...

Optogenetic neural spheroids excite primary neural network.

Journal of neural engineering
Optical stimulation ofneurons requires prior transfection with light gated ion channels. This additional step brings complexity and requires optimization. Simplification of the process will ease the undertaking of studies on biological neural network...