AIMC Topic: Machine Learning

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Predicting egg production rate and egg weight of broiler breeders based on machine learning and Shapley additive explanations.

Poultry science
Egg production rate and egg weight are core indicators for evaluating the production performance of broiler breeders. The accurate prediction of these indicators can significantly enhance farm economic efficiency and can provide a basis for future pr...

Impacts of micro/nano plastics on the ecotoxicological effects of antibiotics in agricultural soil: A comprehensive study based on meta-analysis and machine learning prediction.

The Science of the total environment
Micro/nano plastics (M/NPs) and antibiotics, as widely coexisting pollutants in environment, pose serious threats to soil ecosystem. The purpose of this study was to systematically evaluate the ecological effects of the co-exposure of M/NPs and antib...

Developing a machine learning model with enhanced performance for predicting COVID-19 from patients presenting to the emergency room with acute respiratory symptoms.

IET systems biology
Artificial Intelligence is playing a crucial role in healthcare by enhancing decision-making and data analysis, particularly during the COVID-19 pandemic. This virus affects individuals across all age groups, but its impact is more severe on the elde...

PREPRINT Machine Learning for the Sensitivity Analysis of a Model of the Cellular Uptake of Nanoparticles for the Treatment of Cancer.

International journal for numerical methods in biomedical engineering
Experimental studies on the cellular uptake of nanoparticles (NPs), useful for the investigation of NP-based drug delivery systems, are often difficult to interpret due to the large number of parameters that can contribute to the phenomenon. It is th...

Selective Identification of Hazardous Gases Using Flexible, Room-Temperature Operable Sensor Array Based on Reduced Graphene Oxide and Metal Oxide Nanoparticles via Machine Learning.

ACS sensors
Selective detection and monitoring of hazardous gases with similar properties are highly desirable to ensure human safety. The development of flexible and room-temperature (RT) operable chemiresistive gas sensors provides an excellent opportunity to ...

Application of Raman spectroscopy and machine learning for identification and characterization.

Applied and environmental microbiology
UNLABELLED: an emerging fungal pathogen characterized by multidrug resistance and high-mortality nosocomial infections, poses a serious global health threat. However, the precise and rapid identification and characterization of remain a challenge. ...

Mapping Spatiotemporal Disparities in Residential Electricity Inequality Using Machine Learning.

Environmental science & technology
The move toward electrification is critical for decarbonizing the energy sector but may exacerbate energy unaffordability without proper safeguards. Addressing this challenge requires capturing neighborhood-scale dynamics to uncover the blind spots i...

Data and Molecular Fingerprint-Driven Machine Learning Approaches to Halogen Bonding.

Journal of chemical information and modeling
The ability to predict the strength of halogen bonds and properties of halogen bond (XB) donors has significant utility for medicinal chemistry and materials science. XBs are typically calculated through expensive ab initio methods. Thus, the develop...

Integration of SPEI and machine learning for assessing the characteristics of drought in the middle ganga plain, an agro-climatic region of India.

Environmental science and pollution research international
Drought, as a natural and intricate climatic phenomenon, poses challenges with implications for both natural ecosystems and socioeconomic conditions. Evaluating the characteristics of drought is a significant endeavor aimed at mitigating its impact o...

Machine learning approaches toward an understanding of acute kidney injury: current trends and future directions.

The Korean journal of internal medicine
Acute kidney injury (AKI) is a significant health challenge associated with adverse patient outcomes and substantial economic burdens. Many authors have sought to prevent and predict AKI. Here, we comprehensively review recent advances in the use of ...