سامانه همایش های دانشگاه آزاد اسلامی واحد نجف آباد

صفحه اصلی / اولین همایش بین المللی تحول خدمات سلامت: تلفیق مراقبت، درمان، بازتوانی و امیدبخشی

Hybrid Intelligence in Medicine 3.0: Enhancing Preventive and Curative Decision-Making through AI-Human Collaboration in Personalized Telehealth Systems

نویسندگان :

Hossein Tork Ladani¹ Zahra Shokri Mashhadi² Mahdi Tork Ladani³

1- دانشگاه آزاد واحد نجف آباد 2- دانشگاه اصفهان 3- دانشگاه شاهد

کلمات کلیدی :

Artificial Intelligence،Human-in-the-Loop،Hybrid Intelligence،Medicine 3.0،Telemedicine،Clinical Decision Support،Preventive Healthcare

چکیده :

Background: Medicine 3.0 emphasizes proactive, personalized prevention over reactive treatment, aiming to extend healthspan rather than merely treat disease [1]. Existing AI-assisted clinical systems typically address isolated tasks - diagnostic support, documentation, or risk prediction - without integration into a unified, prevention-first paradigm [2,3], limiting their capacity to support longitudinal proactive care. Method: This study employs a conceptual-analytical framework developed through a scoping review conducted per the PRISMA-ScR extension [4]. A four-agent hybrid intelligence architecture was designed, integrating large and small language models, deep learning, and classical algorithms under a Human-in-the-Loop (HITL) oversight layer [5]. NLP-driven conversational agents perform adaptive anamnesis collection, while LSTM/XGBoost models support continuous risk forecasting. Scenario-based analysis was conducted across the diagnosis/treatment and early-prevention domains. Finding: The architecture comprises Adult and Pediatric Anamnesis Agents for adaptive, red-flag-aware history-taking; an Auto-Documentation Agent generating structured SOAP notes and differential diagnoses; and a Generation-3 Predictive Agent that continuously analyzes wearable biometrics, metabolic markers, and lifestyle data to forecast events such as cardiac risk or nocturnal hypoglycemia via a stratified risk dashboard. Conclusion: The proposed hybrid intelligence framework shifts care from reactive treatment toward proactive, personalized prevention aligned with Medicine 3.0, while preserving clinician oversight. Clinical translation requires attention to data-protection compliance (HIPAA, GDPR) and infrastructural constraints. Prospective clinical trials and expert-panel feasibility assessments are needed to validate real-world efficacy and safety. Keywords: Artificial Intelligence, Hybrid Intelligence, Human-in-the-Loop, Medicine 3.0, Telemedicine, Clinical Decision Support, Preventive Healthcare