Secure and Transparent Lawyer-in-the-Loop Medico-Legal Insurance Decisions by Explainable AI and Blockchain Technology

Legal claims processing requires rigorous verification and extraction of evidence from confidential data. The processing of legal claims by human lawyers can be time-consuming and complex due to the extensive manual work. Explainable Artificial Intelligence (XAI) offers automation potential; however, the ambiguous nature of legal data leads to AI decisional inaccuracies. The paper presents a framework on blockchain and XAI to process the medico-legal claims against medical professionals in the event of medical negligence or malpractice. It meets data protection requirements imposed by GDPR. This hybrid approach ensures data privacy and security across multiple organizations and bridges the AI transparency gap through understandable decisions reviewed by lawyers and data scientists. A lawyer-in-the-loop decision-making system based on evidential reasoning and explainable deep learning is presented. The framework is tested on pre-litigation decisions for clinical negligence of oncologists and is periodically refined using newly annotated low-confidence cases manually assessed by lawyers.