Authors: Dr.S. Thilagavathi, Mohammed Safi TJ, Ms. Diyana Fathima H
Abstract: PLANEXA is a hierarchical reasoning system that aims to assist in medical diagnostic decision-making in a complex clinical environment. PLANEXA structures medical knowledge into multiple levels of reasoning, from basic patient information such as symptoms, vital signs, lab results, and medical history. It progresses to higher-level tasks such as forming diagnostic hypotheses and assisting in clinical decision-making. PLANEXA employs rule-based reasoning, probabilistic inference, and knowledge-driven models to effectively address diagnostic uncertainty and interdependencies among clinical variables. The system's design enables it to decompose complex diagnostic problems into smaller, more tractable sub-problems. This strategy enables efficient reasoning, hypothesis refinement, and learning from new patient data as it becomes available. PLANEXA is also concerned with explainability, as it develops well-defined diagnostic pathways that help clinicians understand why particular diagnoses and recommendations are made. This helps to establish trust, usability, and its integration into the clinical workflow. Results from experimental evaluations conducted on representative clinical cases and standard benchmark problems demonstrate that PLANEXA enhances diagnostic performance, reduces reasoning complexity, and improves decision consistency relative to traditional flat or single-layer models. PLANEXA has immense potential for scalability across multiple domains of medicine and evolving with changes in clinical knowledge. PLANEXA marks an important advancement toward smart, understandable, and dependable AI-driven medical diagnostic support systems that aim to reduce diagnostic errors and improve patient outcomes.
DOI: https://doi.org/10.5281/zenodo.19254441
