AI-DRIVEN EXPERT SYSTEM FOR DYNAMIC DISEASE PREDICTION USING FACIAL EXPRESSION, VOICE PATTERNS AND EMOTIONAL METRICS - Snigdha G, Saraswathi,S, Ashok M, V. Veerakumaran (South Eastern European Journal of Public Health, 2025)
Technology incorporation into the medical field supports to maintain the patient data in digital form to provide productive healthcare services. It supports remotely by enabling humans to consult with healthcare experts without physical presence and non-utilization of facilities. This approach offers the convenient remote access by overcoming significant challenges in providing holistic care based on emotional well-being or mental state during remote interactions. Traditional systems fail to offer personalized expert recommendations tailored to the dynamic needs of the human relying instead on more generalized approaches. This proposed approach introduces an AI-powered healthcare system to overcome these limitations by integrating advanced machine learning techniques such as Temporal Convolutional Neural Networks (TCNN) for facial expression recognition to assess emotional states and Convolutional Neural Networks (CNN) for speech recognition to capture vocal patterns. Furthermore, Natural Language Processing (NLP) is employed to understand the semantic content of patient speech enabling a comprehensive analysis. A key feature of the system is the use of content-based filtering to recommend healthcare expert’s best suited to the specific condition. The integration of secure video consultation services allows for real-time monitoring and assessment of the facial expressions and speech patterns during the consultation. The system also includes a feedback mechanism to continuously improve expert’s recommendations and the performance of the model is enhanced during every prediction. By providing personalized recommendations and real-time emotional insights this AI-driven solution addresses the shortcomings of traditional support services. This system marks a significant step forward in medical field combining machine learning with human-centered care to deliver a better remote healthcare experience.