DIAGNOSURE: AN AI-POWERED HEALTHCARE SUPPORT SYSTEM

Abstract

Abstract - DiagnoSure is an Artificial Intelligence (AI)- powered healthcare support system designed to assist in preliminary disease prediction using patient-provided symptoms. The system addresses the challenge of processing unstructured medical inputs expressed in natural language. A domain-specific Natural Language Processing (NLP) model, BioBERT (Bidirectional Encoder Representations from Transformers for biomedical text), is utilized to extract relevant medical features from free-text symptom descriptions [1]. These features are processed using Extreme Gradient Boosting (XGBoost) to generate disease predictions along with associated probability scores [2]. To ensure transparency and interpretability, SHapley Additive exPlanations (SHAP) is integrated to identify the contribution of individual symptoms to prediction outcomes [7]. The system also supports structured inputs, enabling efficient processing in Electronic Health Record (EHR) scenarios [9]. The proposed approach demonstrates reliable and interpretable predictions and serves as a decision-support tool for early health assessment. Key Words: Artificial Intelligence, Natural Language Processing, BioBERT, XGBoost, Explainable AI, Disease Prediction.

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