Machine Learning Chatbot Development: Bidirectional LSTMs, Advanced NLP Techniques, and Context-Aware Design in a Clinical Information System

Introduction

This paper details the development of the Hypotify Clinical Insights Bot, a context-aware chatbot built with a Bidirectional LSTM architecture, VADER sentiment analysis, spaCy NER, and a 3-turn dialogue state tracker. Trained on 370 labeled clinical intent examples across 20 categories, the system integrates with real patient demographics, hospital admissions, ICD-10 diagnoses, and lab results to deliver live clinical data insights.