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Precision Medicine with Cloud Application Development

  • Boston
  • Healthcare
  • 28 Weeks
  • B2B
  • AWS, Python, TensorFlow, PostgreSQL, Kubernetes

Project Brief

The project’s purpose was cloud application development for precision medicine that combined genetic data with clinical insights, resulting in better patient outcomes for a leading healthcare provider.

Client Background

The client is a prominent healthcare provider that specialises in precision medicine. They concentrate on combining genetic data with clinical information to provide personalised treatment recommendations. They required a robust cloud application to streamline data integration and analysis processes.

Key Challenges:

Integrating several genomic and clinical data sources into a single system was challenging and time-consuming.
Maintain the confidentiality and security of sensitive patient information while adhering to healthcare standards.
Providing real-time data processing capabilities to help in rapid clinical decision-making.
Scalability was required to manage rising data volumes as the customer extended its offerings.
Developing powerful machine learning techniques to extract useful insights from large datasets.
Ensure that the application is highly available and reliable to support important healthcare procedures.

Solution:

1. Discovery and Planning

To better understand the client's needs, our team conducted thorough stakeholder interviews and process analyses. Detailed system requirements were established, and an execution plan with specified milestones and deliverables was developed.

2. Development

We utilized AWS for scalable cloud infrastructure, ensuring compliance with healthcare data regulations. Python and TensorFlow were employed for developing advanced machine learning algorithms. PostgreSQL was used for robust data management, while Kubernetes ensured efficient container orchestration.

3. Implementation

The application was deployed in stages, starting with a pilot to test its functionality and gather feedback. Training sessions were conducted for healthcare professionals to ensure smooth adoption. Continuous integration and deployment practices were followed to provide timely updates and enhancements.

Tools & Technology Used

Python

Programming language

React

Frontend

Tensorflow

Machine Learning Framework

AWS Logo

AWS

Cloud Service

PostgreSQL

Database

Kubernetes

Containerization

Features:

Real-time Data Integration

The programme combines many genetic and clinical data sources in real time, offering a full picture of patient information and allowing for personalised treatment strategies.

High Security and Compliance

Robust security measures and adherence to healthcare legislation assure the protection and privacy of sensitive patient data while retaining trust and dependability.

Advanced Machine Learning Algorithms

Utilizing TensorFlow, the application employs advanced machine learning algorithms to analyze vast datasets, generating actionable insights for precision medicine.

Scalable Infrastructure

AWS delivers a scalable infrastructure that can handle rising data volumes while maintaining high availability and performance as the client's services grow.

Values Delivered:

Enhanced precision medicine capabilities led to more accurate and effective treatment plans.
Streamlined data integration and processing improved overall operational efficiency.
Robust security measures ensured compliance with healthcare regulations and protected sensitive patient information.
Scalable infrastructure supported the client’s expansion, handling increasing data volumes without performance issues.

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