The integration of ML in bioanalytical research offers several advantages:
Efficiency: ML algorithms can process large datasets much faster than traditional methods. Accuracy: ML models can identify subtle patterns and correlations that may be overlooked by human analysts. Scalability: ML solutions can be scaled to accommodate growing datasets without a proportional increase in human resources. Predictive Power: ML can be used to build predictive models for disease progression, treatment outcomes, and more.
