Welcome to COM 42 DevSecOps 2024. This is Praveen Kumar Vallabhoju. I'm a Landovering. And in this session, I'll be talking about integrating cloud technologies for enhanced healthcare system. A comprehensive approach to revolutionizing healthcare efficiency and patient care. Whenever I say cloud technologies, I like to give some examples like AWS, Azure, Google Cloud, and Autoclick Cloud. I'll start with my table of content. It has introduction, challenges in healthcare, proposed solutions, AI seed automation, Kubernetes for scalability, containment with documentum, neural network for AI driven insight, innovate platform benefit, finally, conclusion. Introduction, the need for digital transformation in healthcare, why now healthcare is facing unprecedented challenges in managing massive data volume. The need for timely care and compliance with evolving regulation is growing. Solution. Cloud technologies address these challenges by enabling secure, scalable, and efficient system. Key insight. A unified cloud platform can bridge the gap between technological limitation and healthcare demand. Challenge in healthcare. Current challenges in healthcare system. Key challenges. Data overload. Lack of structure. System for storing and retrieving patient information. System downtime. Even a few minutes of system downtime can jeopardize patient care. Regulatory compliance. Keeping up with HIPAA and other global healthcare standards is resource intensive. Workflow inefficiency. Manual process increases errors and delay critical decision impact. Without modernizing these challenges will escalate as healthcare demand rises. Proposal solution integrating advanced cloud technologies. CACD automation reduces manual intervention and ensures seamless deployment. Whenever I say CACD, it's like tools like GitHub and GitLab. And Kubernetes handles dynamic scaling to meet fluctuating demands. So when I say Kubernetes, it's like EKS, AKS, and other Kubernetes platforms available in the market. very much. organizes structured and unstructured medical data efficiency. in other words, a documentum is an open text product available in the market. It's enterprise level management. Neural network drives insights for diagnostic, imaging, and decision making, which can be achieved using Python libraries like TensorFlow. And other neural network libraries like Keras. Those libraries can help in making the neural network work. Outcome. A unified platform that lowers costs, ensures compliance, and improves patient outcomes. CSED. Automation automating healthcare application deployment. Why does CSED matter? Fast, reliable updates are crucial for mission critical healthcare applications. Automation reduces human errors. and ensure constant deployment. So when I say CRCD, it's like a code commit, manual testing. All these things can be automated in the CRCD platform so that, deliverable will be faster and reliable and secure. And, with the key benefit, 30 percent priority gain, teams can focus on inline automation instead of manual deployment, faster responses, bug fixes, and feature updates, rollouts, in hours instead of days. Thank you. Kubernetes for Scalability Dynamic Resource Management Kubernetes How Kubernetes helps Automatically scales resources based upon their real time demand Ensure critical systems remain operational even during peak usage. So it's like you have a hospital website and it might be need like more resources during the peak time. Kubernetes will help in making autoscale and which brings up the based upon the traffic and CPU configuration we can bring up the application to support with the more parts and when there is low traffic and low usage and based upon the CPU you can bring down the parts usage. So with this we can reduce the. resource, management, which is equal to a benefit, like 40 percent cost reduction only uses resources when needed, optimizing cloud expenses. And it supports zero downtime reliable service for the healthcare professional and patients. which means if we have a new feature, we can just bring up the new feature. Like we thought bringing up with the current application going down totally. We can just bring it up, do the blueprint deployment. which means we can just bring up the newly featured application up and just bring down the old feature down using the pod reduction and bring up the new feature up with more pods. which means We can achieve the zero downtime and without a patient even or persons who are using this application may not even know there is an application went down for the significant amount of time. Example, a hospital can scale its systems during health crisis without overhauling infrastructure. Content management with Documentum. Managing healthcare with Documentum. One Documentum solves. Organizers. Structured and unstructured data allows secure and quick access to critical patient record. So when I say organized structure like lab results, we can just store these lab results and document them using metadata and all other fields. And whenever we enter this data and which is finally helpful for us to return the document quicker than the normal process of finding the document. So with these, the benefit includes like HIPAA compliance document handling ensures data security since it is stored in the enterprise content management. So content management is designed for the providing the security of the document. So it provides the, as for the complexity, provide the security standard and efficiency. Since we have the metadata on this document, we can, it is, helps like finding the document very faster as compared to The normal process. And with this example, document reduces patient record retrieval times by up to 60 percent enabling quicker diagnosis. Neural network for AI driven. So transforming healthcare with neural network. Applications in healthcare. Medical images detect anomalies in x ray and MRI with a human level accuracy. Predictive analysis identify potential outcome. Complications early. Personalized treatment. Suggest treatment plan tailored to individual patient. Impact. Reduces diagnostic errors and support evidence based decision making. Surpasses human performance like tasks like detecting cancer itself. I just want to give some example. So basically where we use neural network. So example of patient A goes to the patient B. perform the CT scan and it may be any way, it is due to, it may be due to the device malfunction or the person who is operating who need more, higher accuracy of the image due to the chance, high chance of, exposing the radiation to the particular patient. So with this neural network, we can easily, you know, detect, is the person exposed to higher radiation and, if it is go, if it goes for the higher radiation, we can start working on the, treatment before it makes go to the cancerous cell. With this slide, I'd like to give the benefit of this platform, unified cloud platform for healthcare. Integrating solutions like CI, CD, Kubernetes, Documentum, and AI for seamless operation benefits workflow automation eliminates redundancies and improves collaboration, cost reduction, pooling resources, lower operational expenses, patient outcome, faster, more accurate diagnosis and treatment, scalable and feature ready, easily adopts new technologies and growing demand. example, hospital adapting unified cloud platform reported 25 percent improvement in patient care efficiency. Conclusion. The integration of advanced cloud technologies into health care system is non step. It's not just a technological shift, but a transformative approach to addressing critical challenges in the industry. By leveraging CI SEED Automation, Kubernetes Documentum, and neural network, SDK organizations can create a unified, scalable, and intelligent infrastructure. This integration optimized workflow ensures compliance with stringent regulations, reduces operational costs, and most importantly, improves patient care outcomes. The unified platform fosters collaboration among healthcare professionals, enhances diagnostic accuracy, and enables timely treatment, laying the foundation for a data driven, patient centric healthcare system as the healthcare landscape continues to evolve with trends like precision medicine and remote monitoring. This integrated approach provides the adaptability and scalability needed to incorporate emerging technology seamlessly. So with this, I would like to thank everyone who gave this opportunity to speak up on these cloud technologies. Thank you and have a great day ahead. Bye.