The healthcare industry, globally, is under competitive and legislative pressure to reduce the cost of care, efficiently manage resources, and improve patient care. Our team of analysts employs data, and advanced analytics tools like deep learning - convolutional neural networks (CNN), Natural Language Processing (NLP) to improve patient care, hospital administration and supply chain efficiencies. These solutions enable healthcare providers minimize cost, improve cash flows and optimize ROIs.
Our solutions in Healthcare Analytics
Diagnostic Image Analytics
- We use deep learning to do diagnostic image analytics and aid radiology, sonology as well as histopathology to make more accurate diagnoses.
- Some of the already developed solutions include diabetic retinopathy, MRI brain scan and ultrasound nerve segmentation.
Hospital Revenue and Bed Space Management
- Predicting future cash flows
- Work Flow Optimization
- Efficient use of hospital resources
- Mortality Prediction
We use patient similarity metric through techniques like KNN, Random Forest, Nnet and digital data for personalized mortality prediction like ICU mortality prediction, MDR infection mortality prediction
- New predictive models can be built using local data.
- Dengue Epidemic – to predict number of dengue cases each week in each location based on environment variables.
- This would help the public health workers and concerned authorities to take steps to reduce impact of these epidemics and also help prepare and build awareness at the right time before it becomes an epidemic.
Our data visualization solutions enable you to derive actionable insights from your complex and vast healthcare data.
Check out our Presentations/Case Studies:
- Data Science for Healthcare: Operational/Administrative
- Data Science for Healthcare: Image Analytics
- Case studies: