This research project aims to develop an innovative "ICU Brain Injury Patient Consciousness Monitoring and Prognosis Decision Support System" to enhance the quality of clinical care and decision-making processes for brain injury patients. This project will create a decision support system for EEG monitoring in intensive care units, leveraging heterogeneous data collection and analysis and advanced artificial intelligence algorithms. By real-time monitoring of patients' brain activity, the system will provide immediate data analysis to assist medical personnel in making more precise clinical decisions. The implementation of this system is expected to improve patient survival rates and quality of life, aid in the rational allocation of medical resources, and reduce the financial burden on patients and families.

This project aims to significantly improve prognosis assessment accuracy and clinical decision support for brain injury patients. The This research will enrich the theoretical foundation and clinical application of EEG analysis and AI in medical prognosis prediction. By establishing a brain consciousness database, it will promote the development of related academic fields and explore long-term care applications, further enhancing the overall care quality for brain injury patients.

Intern Education Level
1. Students who are pursuing bachelor's degrees and are in their final year or students pursuing Master's in Healthcare Informatics, Biomedical Informatics, Computer Sciences, Health, and Life Sciences.
2. Strong knowledge of machine learning, deep learning, and statistical analysis techniques.
3. Hands-on experience with healthcare datasets, including EMR or wearable device data.
4. Excellent problem-solving skills and the ability to communicate technical findings effectively to non-technical audiences.
5. Strong written and verbal communication skills in English.

We offer a project duration of no less than 2 months and no more than 6 months.