Advanced Double Input Layered Neural Network for medical diagnosis by using cloud computing technology

Advanced Double Input Layered Neural Network has the potential to revolutionize medical diagnostics by solving pressing problems. It improves diagnostic precision by providing a single, unified platform for the examination of both organized and unstructured medical data. It provides real-time decision assistance and data management by utilizing the scalable, secure, and efficient data processing capabilities made possible by cloud computing. Improved patient care, more effective therapy, and higher-quality healthcare are some areas where Advanced Double Input Layered Neural Network can make a difference. Rapid, precise, and secure data analysis; the administration of multiple data sources; and realtime decision support are a few of the difficulties inherent in medical diagnosis. This research proposes an Advanced Double Input Layered Neural Network (ADILNN) with a double input layered neural community, enabling it to examine prepared and unstructured scientific data. This novel technique improves the community's mastering functionality from various data kinds. By centralizing statistics garage, processing, and analysis on the cloud, computing sources may be extra reliably accessed whilst wanted. The network's diagnostic precision and flexibility are each advanced through way of tool gaining knowledge of strategies (MLM). Because of its adaptability, ADILNN can be utilized in diverse medical fields, which include radiology, pathology, cardiology, and genetics. It permits examine genomic information, making recovery alternatives, and analyzing x-ray photos. The technique has numerous ability makes use of in healthcare, improving prognosis accuracy in diverse settings. Simulation analysis is used to gauge ADILNN's capacity by way of gauging its diagnostic accuracy, processing speed, scalability, and records protection. These research validate ADILNN's potential to improve clinical analysis, streamline facts management, and guarantee healthcare records's safe and effective utility.