Samanthia Johnson
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Also affiliated: West Virginia University (2026); Delaware Valley College (2026)
Research Areas
Biomedical Subjects
Biography and Research Information
OverviewAI-generated summary
Samanthia Johnson's research focuses on developing predictive models for animal agriculture, particularly concerning feed intake and growth performance in beef cattle. Her work utilizes advanced machine learning techniques, including Long Short-Term Memory (LSTM) networks and Gradient Boosting (GPBoost), to analyze longitudinal data and forecast individual animal water intake and dry matter intake (DMI). This research aims to improve livestock management by providing deployable tools that do not require exact birth dates for accurate predictions. Johnson also investigates the physiological and molecular responses of cattle to dietary interventions and stressors, examining how factors like essential oil supplementation and immune stimulation impact growth performance, plasma metabolomes, and ruminal microbiome composition. Her publications contribute to understanding the biological mechanisms underlying animal productivity and developing data-driven approaches for optimizing animal husbandry.
Metrics
- Publications: 6
Selected Publications
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Deployable DMI prediction using GPBoost, MLOps, and flask without the need for exact birth dates (2026)
Collaboration Network
Top Collaborators
- Deployable DMI prediction using GPBoost, MLOps, and flask without the need for exact birth dates
- Deployable DMI prediction using GPBoost, MLOps, and flask without the need for exact birth dates
- Deployable DMI prediction using GPBoost, MLOps, and flask without the need for exact birth dates
- Deployable DMI prediction using GPBoost, MLOps, and flask without the need for exact birth dates
- Deployable DMI prediction using GPBoost, MLOps, and flask without the need for exact birth dates
- Deployable DMI prediction using GPBoost, MLOps, and flask without the need for exact birth dates
- Deployable DMI prediction using GPBoost, MLOps, and flask without the need for exact birth dates
- Deployable DMI prediction using GPBoost, MLOps, and flask without the need for exact birth dates
- Deployable DMI prediction using GPBoost, MLOps, and flask without the need for exact birth dates
- Deployable DMI prediction using GPBoost, MLOps, and flask without the need for exact birth dates
- Deployable DMI prediction using GPBoost, MLOps, and flask without the need for exact birth dates
- Deployable DMI prediction using GPBoost, MLOps, and flask without the need for exact birth dates
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