Mentor Areas
The Tsui laboratory focuses on real-time clinical AI and machine learning research and deployment. Our research areas include 1) AI machine learning based clinical decision support, 2) natural language processing, 3) mobile Health, and 4) real-time production systems. For clinical decision support, we focus on building predictive models with explanation such as deep neural networks and other machine learning algorithms to detect or predict risks at the patient level or population level, i.e., personalized risk detection or population surveillance. We have developed big-data approach, i.e., working on various data types including electronic heath records (structured and unstructured data), streaming waveform data, and video data. For natural language processing (NLP), we develop deep learning NLP tools to process unstructured (free-text, narrative) reports from the clinical domain (e.g., discharge summary) and social networks (e.g., Twitter messages). For mobile health, we develop mobile apps that collect various data from users and have the capability to interact with the users. For real-time production systems, we translate research to the bedside through the integration of our research models to a real-time production system that provides real-time decision support to frontend clinicians, hospital staff, and users. The lab is located in the Children’s Hospital of Philadelphia working closely with clinicians to advance medical and clinical informatics to the next level.
Description:
We currently have the following ongoing projects:
1. Prediction of critical events in pediatric intensive care and floor patients
2. Prediction of suicidal attempts
3. Prediction of infant mortality and pre-term deliveries
4. Vital-sign waveform (EEG, EKG) analysis and diagnosis
6. Clinical intervention prediction
7. Expert knowledge platform (EKP)
8. Social determinants of health (SDOH) processing using deep natural language processing
Preferred Qualifications
We strongly encourage talented students with some background in programming (e.g., Python, R, Java, and/or Matlab, etc.) to participate in our lab. We welcome students with good communication and writing skill to join us. Students with graphic user interface design experience/interest are also welcome.
Details:
Preferred Student Year
First-year, Second-Year, Junior, Senior
Academic Term
Fall, Spring, Summer
I prefer to have students start during the above term(s).Volunteer
Yes
Yes indicates that faculty are open to volunteers.Paid
Yes
Yes indicates that faculty are open to paying students they engage in their research, regardless of their work-study eligibility.Work Study
Yes
Yes indicates that faculty are open to hiring work-study-eligible students.