Hello, everyone. Welcome to COM 42 I'm the DevOps HR engineer at Landover E. In this session, I'll be talking about integrating cloud technologies for enhanced healthcare system, a comprehensive approach to transforming healthcare infrastructure. To begin with, I'll be talking about integration to cloud integration in healthcare, CICD automation, driving and Productivity in healthcare. Kubernetes for scalable and cost effective healthcare infrastructure. Documentum for advanced healthcare content management. Leveraging AI and neural network for advanced healthcare workflow. Integrated Documentum and Neural Network for workflow automation. Creating a unified cloud platform for healthcare. Future readiness and adaptability of the integrated system. One of the countries. Introduction to Cloud Integration in Healthcare Problem Statement Data management is challenging in healthcare due to the increasing volume and complexity of medical information. Traditional systems are often fragmented, leading to inefficiencies and difficulties in scaling up operations. Regulatory compliance, e. g. HIPAA, imposes stringent requirements on data handling, making robust solutions essential. Thank you for your time. Solution overview. Cloud technologies enable integration of different healthcare processes, ensuring seamless flow of information by leveraging modern tools like CICD, Kubernetes, Documentum, and AI. Healthcare organizations can create a unified platform that is efficient, scalable, and secure. The aim is to improve patient outcome while reducing operation cost and enhancing confidence. CI CD automation driving productivity in health care. Continuous integration, continuous deployment. CI CD in health care. Key feature. Tools like GitHub Actions automate the software lifecycle from development to deployment, ensuring rapid integration and feedback. Docker containers maintain consistent environment across all stages, Reducing. Discrepancies between development and production benefits. The automation of build and deployment process allows healthcare IT teams to release updates more frequently, ensuring application meet evolving medical needs. Reducing manual intervention in deployment minimizes human error leading to 50 percent drop in deployment issue. Kubernetes for scalable and cost effective healthcare infrastructure. Scalable cloud infrastructure with Kubernetes Dynamic Resource Allocation. Kubernetes auto scaling capability allows for resource adjustment based on current demand, ensuring optimal application performance, especially beneficial during high period workloads. During a period of high demand, such as public healthcare emergencies or large scale data processing tasks, high availability, Kubernetes orchestrates workloads across multiple nodes, providing failover capabilities to prevent service interruption. This ensures that healthcare applications remain accessible, reducing the risk of downtime that could impact patient safety. Documentum for advanced healthcare content management. Efficient management of medical data using Documentum. Data organization. Efficient. Effectively manages various types of data from patient demographics to clinical notes and medical imaging. Facilitates unified storage for both structured and unstructured data. Simplifying information retrieval and enhancing interoperability. Compliance and security designed to meet stringent regulations such as HIPAA, ensuring data privacy and security at all time, provides a robust system for tracking document access and modification, enabling detailed audit trails for compliance purpose. Input efficiency reduces the time required to locate critical document and patient records. Thank you. allowing healthcare professional to dedicate more time to patient care. Leveraging AI and neural network for advanced healthcare workflow. AI powered healthcare with neural network pattern recognition, deep learning models such as convolutional neural network can detect complex pattern in radiology images, potentially diagnosis conditions more accurate than human radiologists. Predictive decision making. Any algorithm can predict patient outcome by analyzing historical data, enabling personalized treatment plan and early intervention for conditions like diabetes or heart diseases. Workflow automation. Automates repetitive tasks such as sorting medical records, or prioritizing patient for treatment. Streamlining administrative workflows. Integrating Documentum and Neural Network for Workflow Automation. Intelligent Workflow Automation in Healthcare Automated Document Workflows uses metadata which triggers initial processes automatically, such as updating patient EHRS when new information is added or generating alerts for missing information. AI enhanced recommendation. Suggest diagnostic tests or treatment based on pattern identified on the patient data. Improving critical clinical decision making. Recommendation workflow optimization based on historical data. Enabling better resource utilization. Creating a unified cloud platform for healthcare. Seamlessly integration of cloud technologies for healthcare transformation. Unified approach. Centralizes various healthcare applications and processes on a single platform, ensuring all components work together efficiently. Integrates tools for development, CI, CD, deployment, governance, data management, documenting, and AI to create a holistic solution. Workflow automation automates and streamlines operations such as updating records, processing Managing patient appointment eliminates information silos by making data accessible across departments, improving collaboration and patient care. Featured readiness and adaptability of integrated system. Preparing healthcare system for future challenges. Scalability. Easily expands to handle increased patient volume, new healthcare application, and more complex data processing needs. Flexibility. Support the integration of new technologies such as wearable devices for remote patient monitoring genomic data analysis. Sustainability provides a foundation for long term innovations in healthcare including precision medical medicine and AI enhanced diagnostics. Ensures that the system evolves with illicit and without the need of Frequent large scale upgrade. Conclusion. Cloud integration offers pathway to more efficient data driven healthcare system capable of reducing cost and improving patient outcome. The combined benefits of CICD, Kubernetes, Documentum, and AIP today future proof our healthcare infrastructure. And this concludes my session and thank you very much for giving this opportunity and Please enjoy your next conf42 talks and thanks. Thank you very much. Bye.