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Clinical Informatics
Clinical informatics is the applications of informatics principles and methods in the delivery healthcare services. This includes advanced electronic medical record (EMR) systems, computerized clinical decision support systems, wearable technology and mobile health (mHealth) applications, and reuse of EMR, study and molecular data for improving healthcare delivery. In Department of Biomedical Informatics, the focus is on development and application of artificial intelligence, computational and data science methods to advance clinical informatics. Two departmental centers provide training, staff, and resources. The Center for Clinical Informatics (CCI) is focused on focused on the application of informatics to deliver healthcare services. The Center for Clinical Research Informatics (CCRI) is focused on the application of informatics for the reuse of clinical, mHealth, molecular and research data to enable clinical, translational, and informatics research.
Areas of research include
- developing intelligent electronic medical record systems
- developing clinical decision support systems for alerting on anomalous physician orders, prediction of readmission,
- personalized modeling for precision medicine that includes developing algorithms for predicting clinical outcomes and sub-phenotyping
- providing explanations for predictions by statistical and machine learning models
- developing decision support using wearable technology and mobile health (mHealth) applications
- approaches to close the Learning Health System loop
Opportunities for research are available at various stages of training
- For high school students through the summer Computer Science, Biology and Biomedical Informatics (CoSBBI) program
- For undergraduate students through Capstone projects in Computer Science and Bioinformatics majors
- For medical students through Areas of Concentration (AoC) program in Bioengineering, Biotechnology, and Innovation
- For MD/PhD trainees in the biomedical informatics graduate program
- For residents and fellows through research rotations
- For graduate students in biomedical informatics, the Intelligent System Program (ISP), and computer science
- For post-docs with graduate training in biomedical informatics, computer science, artificial intelligence, statistics, machine learning and related disciplines
Knowledge and skills in the following areas are desired
- Probability and statistics
- Computer science and programming
- Machine learning and data science
- Experience with medical data (especially EMR data)
Contact
Shyam Visweswaran, MD, PhD
Director of Clinical Informatics, Department of Biomedical Informatics
Email: shv3@pitt.edu