Risk Score

Risk scores are quantitative assessments of the likelihood of an undesirable outcome, used across diverse fields to guide decision-making and resource allocation. Current research focuses on improving risk score accuracy and interpretability using various machine learning techniques, including gradient boosting machines, neural networks (both traditional and interpretable variants), and embedding methods like node2vec for graph-structured data. These advancements are impacting diverse sectors, from healthcare (predicting disease progression and treatment response) and finance (credit risk assessment) to cybersecurity (IoT device vulnerability prediction) and education (identifying at-risk students), enabling more effective and targeted interventions.