11th International Conference on ICTIS

Authors - Niraja Jain, Rajeev Kumar, Golnoosh Manteghi
Abstract - Medical negligence litigation in India poses significant challenges to the justice delivery system due to the complexity of clinical evidence, fragmented legal documentation, and limited availability of structured decision-support mechanisms for legal practitioners. These challenges often result in delays, inconsistent legal reasoning, and increased cognitive burden on judges and lawyers handling medico-legal disputes. This paper presents the design and preliminary validation of a Judicial Decision Support System (JDSS) tailored specifically for medical negligence litigation in the Indian legal context. The proposed JDSS leverages advanced Natural Language Processing (NLP) techniques and supervised machine learning models to assist early-stage legal triage through automated case summarization, statutory section prediction, and precedent recommendation. Transformer-based language models are fine-tuned on publicly available Indian legal judgments and augmented with a domain-specific legal–medical ontology to bridge semantic gaps between clinical narratives and legal reasoning. Explainability is embedded at both the model and user-interface levels through attention visualization and feature attribution mechanisms, addressing transparency requirements critical for high-stakes judicial applications. The system has undergone formative evaluation through an exploratory stakeholder survey involving participants from legal, academic, and higher-education ecosystems in India. This evaluation focuses on perceived usefulness, trust, explainability expectations, and institutional readiness for AI-assisted judicial tools, rather than predictive performance. Findings from the survey informed key design choices, particularly the emphasis on explainable AI and modular deployment. While large-scale retrospective evaluation on real-world court data remains part of future work, the current study establishes a methodologically grounded and ethically aligned foundation for AI-assisted judicial decision support in resource-constrained legal environments, with scope for integration into India’s evolving digital judiciary infrastructure.