Case study

AI-Powered Personalized Healthcare Platform

Stack

Python, TypeScript, TensorFlow, PyTorch, Scikit-learn, Apache Kafka, Apache Spark, PostgreSQL, Snowflake, Amazon Redshift, AWS (S3, EC2, RDS), Google Cloud Platform (GCS), Docker, Kubernetes,

DURATION

18 months

TEAM SIZE

1 Solutions Architects, 3 Backend Developers, 2 Frontend Developers, 2 QA Engineers

Our Client:

Our client is a healthcare provider in the US. They’re always looking for new ways to make patients healthier. They saw how much data could help change preventive care and create medical plans tailored perfectly to each person.

fastapi

FastAPI

OpenAI GPT-4

LangChain

ChromaDB

python

pyTesseract

Azure

Stack:

  • Programming Languages: Python, TypeScript
  • AI/ML Frameworks: TensorFlow, PyTorch, Scikit-learn
  • Data Processing: Apache Kafka, Apache Spark
  • Database/Data Warehousing: PostgreSQL, Snowflake, Amazon Redshift
  • Cloud Platform: AWS (S3, EC2, RDS), Google Cloud Platform (GCS)
  • Containerization & Orchestration: Docker, Kubernetes
  • Web Frameworks: React.js, Flask, Django
  • Integration Standards: HL7 FHIR
  • Security: OAuth2, RBAC, Encryption (TLS, AES-256)
  • Monitoring & Logging: Prometheus, Grafana, ELK Stack

The Problem

They came to us with a familiar, yet challenging, problem: they had vast amounts of patient information, but it was scattered across different systems and not being utilized effectively. Their usual methods of care, while suitable for most people, couldn’t provide the detailed insights required for truly personalized medicine.

They needed a strong, flexible system that could consolidate all kinds of data, run intelligent AI tests on it, and keep all that sensitive patient information completely secure. Their main goal? To provide highly personalized treatment and preventive plans, which would significantly improve the health of patients and the smoothness of their care.

The Solution

Our team built an advanced AI-powered Personalized Healthcare Recommendations Platform. It’s a knowledgeable health guide that continually learns and adapts to each patient’s needs.

We have developed a comprehensive system that leverages extensive patient data, including electronic health records (EHRs), real-time information on daily life, and detailed genetic data, to deliver clear, highly personalized healthcare advice.

What It Does & How It Works

We built our solution with top-notch technology, focusing on what modern healthcare truly needs:

Pulls All Your Health Information Together:

It smoothly gathers data from EHR systems (using HL7 FHIR), wearable devices (such as smartwatches), and even genetic testing platforms. We used Apache Kafka to handle incoming data at a high rate and Apache Spark to process it efficiently.

Smart AI Brain:

Smart AI Brain: This is where the powerful AI comes in. Our team used advanced machine learning models (like TensorFlow, PyTorch), including deep neural networks. We also utilized Natural Language Processing (NLP) to analyze notes from doctors and specialized tools for genetic data. For reliable growth, we used Docker and Kubernetes.

Your Health Plan:

The system creates tailored plans for preventive care, specific treatment steps, and helpful lifestyle changes, all based on each person’s health risks. It also includes proven medical advice and tools to help doctors make decisions.

Keeps Your Data Super Safe:

We ensured that patient data is incredibly secure. We built encryption to comply with HIPAA rules. We also implemented role-based access control (RBAC), ensuring that only authorized personnel can view specific data and conduct regular security checks. We store data securely using AWS S3 and Google Cloud Storage.

Easy for Doctors to Use:

We created a user-friendly, fast website (built with React.js) for healthcare providers. This allows them to view all the personalized advice easily. The backend, which handles a significant amount of work, was built using Python (Specifically, Flask and Django).

Results:

The platform made a big difference right away, completely changing how our client gives care:

  • 30% more patients stuck to their preventive care plans. That’s a massive step towards better healthcare.
  • It made risk checks 20% more accurate, enabling doctors to plan treatments more effectively.
  • Doctors became 15% more efficient because they had quick access to clear information and innovative tools.
  • Crucially, we observed a 10% drop in hospital visits that could have been prevented, resulting in healthier patients and cost savings.
  • Our client’s reputation continued to grow even stronger as a leader in innovative, patient-focused healthcare.

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