A recent study by Nabrawi & Alanazi (2023) demonstrates how machine learning can combat healthcare fraud in Saudi Arabia. Using techniques like Random Forest (RF), Logistic Regression (LR), and Artificial Neural Networks (ANN), the models achieved impressive accuracy rates (RF: 98.21%, LR: 80.36%, ANN: 94.64%). Key fraud indicators? Policy type, education, and age. Fraud in healthcare drains resources and raises costs, but ML offers a game-changing, efficient solution.

Read more here: https://www.mdpi.com/2227-9091/11/9/160

#MachineLearning #HealthcareFraud #AI #DeepLearning #HealthTech #DataScience #FraudDetection #InsuranceTech #RandomForest #ArtificialNeuralNetworks #PredictiveAnalytics