Intelligence applied

Wearable technology in knee braces is a promising new approach to provide biometric feedback that may allow patients to rehabilitate more effectively from knee injuries and after knee surgery.

Machine learning (ML) has enormous potential to act as a diagnostic adjunct within gynaecology to tackle two main issues: diagnostic uncertainty and delayed diagnoses.

This initiative aims at using different frequency signals to achieve Synthetic UPsampling ARray (SUPAR) to improve angular resolution in multitude. Artificial intelligence (AI) tools will be employed for real time probing design and imaging.

“Human and machine auditory perception” Research into intelligent spatial audio and human perception using machine learning, neuroscience, signal processing, and applied mathematics.

We believe that AI can help address the growing and unmet global needs for highperformance healthcare and wellbeing and lead us towards smarter, sustainable societies in general.

This initiative brings together researchers and scientists in the field of machine learning based image analysis. The aim is to develop new computational tools for improving image-based detection and diagnosis of disease.

This research will focus on developing modular and adaptive algorithms and tools that use sensory observation and measurement data and healthcare records to extract actionable information for effective and timely interventions.