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clinical-informatics [2017/10/29 21:00]
shyam |
clinical-informatics [2019/10/13 09:28]
shyam [Example projects] |
| ===== Clinical Informatics ===== | ===== Clinical Informatics ===== |
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| 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 [[http://www.dbmi.pitt.edu/|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 [[http://www.cci.thevislab.com/|Center for Clinical Informatics (CCI)]] is focused on focused on the application of informatics to deliver healthcare services. The [[http://www.ccri.thevislab.com/|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. | Clinical informatics is the application of computing methods including artificial intelligence in the delivery healthcare services. Predictive and causal models using big data and artificial intelligence will be increasingly used in clinical decision-making. These models will power a new generation of clinical decision support tools in the coming decade. The [[http://www.ccri.thevislab.com/|Center for Clinical Research Informatics (CCRI)]] in the [[http://www.dbmi.pitt.edu/|Department of Biomedical Informatics]] focuses on the development of clinical decision support tools that aid in very specific clinical tasks and are powered by predictive and causal models. |
| | ==== Example projects ==== |
| | * The [[http://www.thevislab.com/lab/doku.php?id=lemr|Learning Electronic Medical Record (LEMR) system]] is an intelligent EMR system that highlights relevant patient data in the EMR in the Intensive Care Unit. The LEMR system uses predictive models to draw the physician’s attention to the right data of the right patient at the right time. |
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| ==== Areas of research include ==== | * Deciding whether to attempt salvage of an infected central venous catheter (CVC) can be challenging. We are developing predictive models to predict retention of CVC lines. A clinical decision support tool that is powered by predictive models will help clinicians in making decisions about infected CVC lines. |
| * developing intelligent electronic medical record systems | |
| * developing clinical decision support systems for alerting on anomalous physician orders, prediction of readmission, | * Realtime intraoperative neurophysiological monitoring is used to identify adverse brain events during surgical procedures. We are developing predictive models to identify adverse events using intraoperative neurophysiological monitoring. A clinical decision support tool that is powered by predictive models will aid neurophysiologists in intraoperative monitoring. |
| * 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 | |
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| ==== Opportunities for research are available at various stages of training ==== | ==== Opportunities for research are available at various stages of training ==== |
| * Probability and statistics | * Probability and statistics |
| * Computer science and programming | * Computer science and programming |
| * Machine learning and data science | * Artificial intelligence and machine learning |
| * Experience with medical data (especially EMR data) | * Experience with medical data |
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| ==== Contact ==== | ==== Contact ==== |