HealthTech AI Integration

Delivering personalized health care through AI-powered diagnostics for global health solutions.

Overview

The xmixde team collaborated with a global healthcare organization to create AI tools to enhance health diagnostics using artificial intelligence to help diagnose diseases faster and more accurately.

Overview

Project Overview

Our team of specialists developed a state-of-the-art AI-powered diagnostic tool using machine learning to analyze patient data from EHR systems for early disease detection and treatment planning.

Project Lead: Dr. Jane Roberts, AI Lead 48
Project Start: July 2023 20 months

Solutions Offered

Objective

Create an AI-powered tool for medical practitioners to streamline diagnosis, improve accuracy and reduce patient care costs and consultation time.

Our Solution

We developed a deep learning model integrating NLP for EHR processing, AI-driven predictive models for disease diagnostics and real-time patient monitoring and early alert systems for clinicians.

Challenges

Challenge: High data variability

Managing the diversity of patient data to ensure robust model training with high accuracy and low false diagnosis errors.

Solution: We developed a dynamic AI model for continuous data integration to handle real-time data stream analysis. Our solution allows for fast, secure patient evaluation, reducing error margin to 1% below average error in traditional methods.

Project Lead

Dr. Lillian Smith

Lead AI Architect

Technologies Used:

Python, TensorFlow

AI Health Informatics

+ 500+

Patients processed monthly for testing

3.3% accuracy rate increase
See full report

Project Outcomes

Improved Diagnosis Accuracy by

40%

Cost savings

120M saved by early disease detection

per year

Healthcare

22 Hospitals using

AI-assisted diagnosis system

Healthcare system

150+

users

Disease Detection

Accuracy

98.4%

accuracy in Early Detection System

Diabetes Prediction

Accuracy:

93%

98.4%

Accuracy in Early Diabetes Detection