A Review on Bone Fracture Detection Techniques using Image Processing

Proactive System Maintenance: Machine Learning Models for Predicting and Preventing Potential System Failures

“…By leveraging machine learning algorithms, it becomes possible to analyse large volumes of sensor data, identify patterns indicative of impending failures, and take pre-emptive action to mitigate Risks. However, the development and deployment of effective proactive maintenance systems require careful consideration of various factors, including data quality, model accuracy, and scalability [7] [8].…”

“…The choice of algorithm depends on factors such as the nature and complexity of the problem, the size and quality of the avail-able data, computational requirements, interpretability of the model, and specific performance requirements. Each algorithm has its strengths and limitations, and the selection should be informed by the unique characteristics and needs of the proactive maintenance system, ensuring that the chosen models align with the overarching objectives while delivering accurate and actionable insights for fault prediction and preventive maintenance operations [7] [9] [10].…”

“…Once the models have been trained, they must be evaluated using appropriate performance metrics to assess their predictive accuracy and generalization ability [7]. This typically involves splitting the data into training and testing sets, training the models on the training data, and evaluating their performance on the unseen testing data.…”