HistoAssist: A Production-Ready Full-Stack AI Framework Bridging Deep Learning Histopathology and Empathetic Patient Communication

Abstract: Artificial intelligence has significant potential in digital pathology, but its practical use is often limited due to issues like secure user access, lack of auditability, and difficulty in explaining results to patients. This work introduces HistoAssist, a ready-to-deploy diagnostic system designed to overcome these challenges. It combines a lightweight CNN built with TensorFlow/Keras to classify histopathology images as benign or malignant, along with a FastAPI backend that provides JWT authentication, secure data handling, and automated report generation. A React.js frontend supports smooth clinical interaction, while a rule-based NLP chatbot explains medical outcomes in simple and empathetic language. HistoAssist goes beyond a research prototype by providing a complete and deployable solution for modern telepathology.

Keywords: Deep Learning, Digital Pathology, Patient-Centred Care, Medical Image Analysis, RESTful Architecture, Artificial Intelligence, Histopathology