CliniScan+: An Integrated AI – Based Lung Disease Detection Diagnosis and Smart Healthcare Support System

lung diseases are among the major health conditions requiring timely diagnosis and appropriate medical consultation. Chest X-ray imaging is widely used as an initial diagnostic investigation; however, conventional analysis depends heavily on expert interpretation and may be time-consuming. Existing artificial intelligence-based diagnostic systems primarily focus on disease classification and often provide limited integration with healthcare support services. This paper presents CliniScan+, an integrated AI-based healthcare support system for lung disease detection using chest X-ray images. The proposed system employs a Convolutional Neural Network (CNN) for automated multi-disease classification and YOLOv11 for visual localization of relevant regions in chest X-ray images, thereby providing an interpretable representation of the model output. In addition to AI-based image analysis, the system incorporates a doctor recommendation module that assists users in identifying suitable medical specialists based on the predicted condition. A consultation tracking module maintains appointment and follow-up information to support continuity of healthcare services. The system is implemented using a Python-based backend and MongoDB for data management. The integration of disease classification, visual explanation, doctor recommendation, and consultation tracking provides a unified healthcare-support platform rather than an isolated prediction model. Experimental evaluation is performed using classification and detection metrics to assess the performance of the implemented models.