Ongoing Project

Utilizing advanced AI algorithms to analyze EEG data for early detection and diagnosis of neurodevelopmental disorders such as autism and ADHD.

Integrating computer vision techniques to analyze facial expressions and behaviors to enhance diagnosis accuracy.

Developing AI models that analyze patient data to recommend personalized treatment plans.

Using signal processing techniques to monitor and predict patient responses to treatments in real-time.

Creating AI-powered wearable devices that continuously monitor vital signs and detect anomalies.

Implementing computer vision for fall detection and activity monitoring in elderly patients.

Applying AI to improve the accuracy and speed of medical image analysis for detecting tumors, fractures, and other conditions.

Developing computer vision algorithms for automated segmentation and classification of medical images.

Integrating EEG with other sensory inputs (auditory, visual, tactile) to develop robust BCI systems for communication and control.

Exploring the use of olfactory and gustatory stimuli in BCI applications.

Using machine learning to predict patient outcomes and prevent hospital readmissions.

Developing predictive models for the spread of infectious diseases and resource allocation.

Creating AI-driven rehabilitation programs tailored to individual patient needs, using data from motion sensors and computer vision.

Implementing virtual reality environments to aid in physical therapy and cognitive rehabilitation.

Developing AI tools for remote diagnosis and consultation, improving access to healthcare in underserved areas.

Using signal processing to ensure the quality and reliability of telemedicine services.