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clinical-informatics [2019/10/13 09:28] shyam [Example projects] |
clinical-informatics [2019/10/13 10:23] (current) shyam |
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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:// | 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:// | ||
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+ | ==== Pipeline ==== | ||
+ | * Step 1: develop models - Develop artificial intelligence models with excellent performance for a tightly specified clinical task | ||
+ | * Step 2: engineer decision support tool - Build decision support tool that applies models developed in step 1 to clinical data in real time | ||
+ | * Step 3: evaluate prospectively - Evaluate decision support tool prospectively to establish efficacy and effect on clinical outcomes | ||
+ | * Step 4: obtain certification and deploy clinically - Obtain FDA certification and license and deploy clinically | ||
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==== Example projects ==== | ==== Example projects ==== | ||
* The [[http:// | * The [[http:// | ||
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* 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. | * 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. | ||
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==== Opportunities for research are available at various stages of training ==== | ==== Opportunities for research are available at various stages of training ==== | ||
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* For graduate students in [[http:// | * For graduate students in [[http:// | ||
* For post-docs with graduate training in biomedical informatics, | * For post-docs with graduate training in biomedical informatics, | ||
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==== Knowledge and skills in the following areas are desired ==== | ==== Knowledge and skills in the following areas are desired ==== | ||
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* Artificial intelligence and machine learning | * Artificial intelligence and machine learning | ||
* Experience with medical data | * Experience with medical data | ||
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==== Contact ==== | ==== Contact ==== |