Driving better health outcomes.

A Machine Learning Pipeline

Genetica Serves as a Machine Learning Pipeline or AutoML to automate the process of applying machine learning to real-world decisions.

Former hockey great Wayne Gretzky was once asked what made him so good because he wasn't the fastest player and did not have the hardest shot? His answer: "I skate to where the puck is going to be, not where it has been." Data driven, predictive AI enables healthcare organizations to make decisions based on what the future holds. In today's rapidly changing world, the past is not necessarily the best predictor of the future. Gone are they days when healthcare organizations could assure success by relying on what was successful in the past when planning for the future.

The GeneticaAI Cortex Cognitive Engine© is a fully integrated end-to-end cloud-based AI application development and lifecycle management platform.

Cortex is a platform for generating domain-specific enterprise-class scalable mobile and web applications with built-in services for AI/machine learning, IoT, data lakes, GIS, and data mining.

Cortex supports domain experts to design, generate, deploy, and manage microservices and mobile apps that can communicate with each other and form complex applications utilizing language-agnostic APIs.

All external computing components of our platform are best-of-breed and open-sourced, ensuring the platform’s future proofing. It operates as a self-organizing computing cluster with a high degree of linear scalability. Its middle-tier application logic layer runs under a Node runtime environment. It can be configured to run on as many computing hosts as needed while maintaining and managing its “cluster state” via Kafka streaming engine. Data-tier runs on the back of MongoDB scalable sharding and replication architecture.

Instead of monoliths, Genetica’s applications are decomposed into smaller, decentralized services. These services communicate through APIs or by using asynchronous messaging (MQTT and Kafka). Applications scale horizontally, adding new instances as demand requires.

The platform’s runtime environment is built for data-intensive, real-time applications, meaning it is single-threaded, event-driven, and designed for elastic scale and automated self-management.

The application state is distributed in a self-organizing cluster of nodes. Operations are done in parallel and asynchronously. The system as a whole is resilient when failures occur. Deployments are automated and predictable. Monitoring and telemetry are built-in for gaining insight into the system.

Identifying Disease and Diagnosis

  • Outbreak prediction
  • Enhanced ED triage
  • Reduction of readmission incidents

Self Diagnosis Capability

  • Images analysis
  • Self monitoring of skin cancer via mobile applications

Improved Medical Imaging Diagnosis

  • Beyond the human eye

Personalized Medicine

  • Moving away from one-size-fits-all to tailored treatment plans based on patient DNA

Learning Health Systems

  • Advance the evidence base for clinical care

Survival Analysis

  • Identify high risk patients to activate preventive measures to optimize health outcomes

AI: Far-Reaching Impact

Improve patient outcomes, gain greater efficiency, and reduce costs

In the years ahead, AI is poised to transform care delivery and administrative operations. In addition to the care delivery examples featured above, other instances could include accounting, finance, and cybersecurity optimization.

Yet, despite the promise presented by AI, for most organizations creating actionable use-cases with analytics and machine learning is a challenging task. The challenge is heightened an acute shortage of data scientists, and by the dependence on those costly technical skills to deliver the capabilities required. In that difficult scenario Genetica's capabilities makes a difference.

Genetica allows non-experts to use machine learning models and techniques without becoming an expert in this field first! Using Genetica is as simple as ‘Drag n Drop’. With an intuitive UI and zero programing requirement, its features and capabilities are ideal. The process of developing, deploying, and maintaining industrial-strength AI applications are reduced by a factor of ten - both in cost and in time.

Genetica AI is available through a seamless integration with the Intersect On FHIR integrated data platform.

U.S. Patent Pending

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