The integration of mobile technologies with intelligent healthcare solutions has the potential to improve accessibility, patient engagement, and early disease detection. Traditional healthcare applications often lack comprehensive features that combine diagnostics, patient management, and real-time community support. To address this gap, this paper present MedGenie, a cross-platform healthcare application developed using Flutter, Dart, and Firebase, designed to provide a unified and responsive experience across Android and iOS platforms. The system incorporates an autoencoder- based deep learning model to analyze medical scans for conditions such as brain tumors, supporting early diagnosis. In addition, MedGenie offers a Report Manager for secure storage of medical records, Medication Reminders to improve treatment adherence, and a community-driven blood request system to enable real-time donor and recipient connections. A chatbot interface is also integrated to provide instant support and enhance user interaction. Experimental evaluation demonstrates the effectiveness of the autoencoder in identifying anomalies from medical scans, while usability tests confirm improved patient engagement and accessibility. By integrating intelligent diagnostics, cloud services, and community support features, MedGenie highlights the potential of mobile health applications in delivering affordable, scalable, and proactive healthcare solutions.