Predictive Healthcare Analytics Platform
Predictive Healthcare Analytics Platform and solutions is a part of advanced analytics which is used to predict future events. Predictive analytics practices numerous ways from data mining, statistics, modeling, machine learning, and artificial intelligence to examine current data to make forecasts about the future.
- Good healthcare helps the economy of the country. Exactness drug alongside Big Data is leveraging in building better patient profiles just as predictive models to diagnose and treat diseases.
- TeleMedicine and AI in healthcare is in fact a marvel remotely performing treatment of patients using Pattern Recognition, optimizing duty allocation, monitoring live data.
- Real-Time Big Data for Infection Control to predict and prevent infections through networks creating safer environments.
- Patient Data Analytics for a patient dealing and preventing readmissions and better pharmaceutical supply chain management and delivery.
Challenges for Building Predictive Analytics Platform
- Interface for the patient to search nearby doctor by particular Healthcare categories.
- Enable patient visibility to see doctor’s availability online and communicate via text chat, audio or video call.
- Visible allotment number to the patient in the waiting queue.
- Communicate with the doctor as well as test or medicine suggestion to the patient.
- Interface for the patient to contact with nearby labs to collect a sample and upload test reports on server followed by the push notification when the report is ready.
- Share report with doctor followed by prescription to the patient.
- Search for nearby medical stores and place an order for the prescription got from the doctor.
Solution Offerings for Real-Time Monitoring
Develop a Healthcare platform to fully automate using the latest technologies and distributed Agile development techniques.
Real-Time Monitoring of User’s Events
Apache Kafka and Spark Streaming to achieve high concurrency, set up low dormancy messaging platform Apache Kafka to receive Real-Time user requests from REST APIs (acting as Kafka producer).
Apache Spark streaming (preparing and processing motor) Spark-Cassandra connector, put away 1 million events per second in Cassandra. Built Analytics Data Pipeline using Kafka and Spark Streaming to capture user’s clicks, cookies, and other data to know users better.
Microservices using Spring Cloud, NetFlix OSS, Consul, Docker, and Kubernetes
Develop REST API’s using Microservices architecture with Spring Cloud and Spring Boot Framework using Java language. Moreover, use Async support of the Spring framework to create Async controllers that make REST API effectively versatile.
Spring to deploy REST and use Kubernetes for secure container and its management. For API passage, use NetFlix Eureka Server which goes about as an intermediary for REST API and the part of Microservices, Consul as DNS empowers auto-revelation of Microservices.
Predictive Analytics Platform for healthcare
Building Big Data Based Healthcare Platform
Healthcare sector manages patient health as well as innovates medicine carving Health industry with Enterprise Data Warehouse, customizable Predictive Modeling, Cloud Driven Analytics, Customer-Centric Solutions, Healthcare Business Intelligence, Smart Healthcare insights, Predictive Analytics, high-performance computing, of sicknesses, detection of diseases, bridging the gap between patient and hospital.
Big Data adds to Healthcare in following manners –
- Healthcare tracking to track user’s statistics, Continuous Monitoring with sensor data collection, identification of health issues.
- Adaptive Data Architecture and Data Warehouse solutions for efficient Healthcare services, quality, and operational services.
- Prevention of Patient Self Harm and Prediction of Patient Utilization Patterns to avoid severe incidents by providing emergency departments and urgent centers with staff optimization.
- Supply Chain Management to ensure better delivery and utilization using automated and Data-Driven solutions optimizing ordering process.
- Data Security assurance to highlight intruder, perform Risk Scoring, Defense Management through Machine Learning and Artificial Intelligence techniques.
- Precision, Telemedicine and New Therapies for better treatments and disease predictions improving outcomes.
- Patient Engagement and Satisfaction improving customer retention, long-term engagement as well as reducing risk.