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AI-Powered Medical Guidance and Treatment Cost Estimation System
0
Zitationen
6
Autoren
2025
Jahr
Abstract
Healthcare accessibility remains a major concern, especially in rural and resource-limited regions where patients face delays in identifying specialists, understanding possible medical conditions, and planning for treatment expenses. This paper presents an AI-driven healthcare guidance framework that integrates symptom interpretation, risk prediction, specialist referral, and cost estimation within a unified platform. The system employs Natural Language Processing (NLP) for structured symptom analysis, a Support Vector Machine (SVM) classifier for condition prediction, and a fine-tuned Large Language Model (LLM) for conversational medical guidance. In addition, the platform retrieves real-time cost information using structured datasets and APIs to ensure financial transparency. Designed as a lightweight, multilingual web application, the system aims to empower patients with timely medical insights, reduce unnecessary hospital visits, and provide reliable cost forecasts, ultimately improving healthcare access and affordability.
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