Authors: Nithish Kumar R, Gokul Kanna Sm
Abstract: Smart Healthcare represents a transformative shift in modern medical systems by integrating artificial intelligence (AI), machine learning (ML), deep learning, and Internet of Things (IoT) technologies into healthcare delivery. Early disease detection, accurate diagnosis, and personalized treatment remain critical challenges in healthcare systems worldwide. Traditional healthcare practices largely rely on manual diagnosis, clinician expertise, and time-consuming diagnostic procedures, which may lead to delayed detection, human error, and increased healthcare costs. With the rapid growth of AI and medical imaging technologies, automated disease detection and health monitoring systems have gained significant attention. Medical images such as X-rays, MRI scans, CT scans, ultrasound images, and skin lesion images contain rich visual information that can be effectively analyzed using machine learning and deep learning techniques. This paper presents an intelligent Smart Healthcare framework that utilizes AI-driven medical image analysis for early disease detection and clinical decision support. The proposed system includes image acquisition, preprocessing, feature extraction, disease classification, and result visualization. Experimental studies indicate that AI-based healthcare systems significantly improve diagnostic accuracy, reduce workload on healthcare professionals, and enhance patient outcomes. The system aims to support early diagnosis, reduce medical errors, optimize treatment planning, and promote efficient and patient-centric healthcare services.
