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research [2018/06/02 08:31]
shyam [Precision medicine and personalized modeling] |
research [2018/06/13 09:58]
shyam [Precision medicine and patient-specific modeling] |
| In predictive modeling in medicine, the typical paradigm consists of learning a single model from a database of individuals, which is then applied to predict outcomes for any future individual. Such a model is called a population-wide model because it is intended to be applied to an entire population of future individuals. In contrast, patient-specific modeling focuses on learning models that are tailored to the characteristics of the individual at hand. Patient-specific models that are optimized to perform well for a specific individual are likely to have better predictive performance than the typical population-wide models that are optimized to have good predictive performance on average on all future individuals. Moreover, patient-specific models can identify features such as genomic factors that are specific for an individual thus enabling precision medicine. This work is in collaboration with [[http://www.dbmi.pitt.edu/person/gregory-cooper-md-phd|Gregory F. Cooper]] (at the University of Pittsburgh). The areas of focus include: | In predictive modeling in medicine, the typical paradigm consists of learning a single model from a database of individuals, which is then applied to predict outcomes for any future individual. Such a model is called a population-wide model because it is intended to be applied to an entire population of future individuals. In contrast, patient-specific modeling focuses on learning models that are tailored to the characteristics of the individual at hand. Patient-specific models that are optimized to perform well for a specific individual are likely to have better predictive performance than the typical population-wide models that are optimized to have good predictive performance on average on all future individuals. Moreover, patient-specific models can identify features such as genomic factors that are specific for an individual thus enabling precision medicine. This work is in collaboration with [[http://www.dbmi.pitt.edu/person/gregory-cooper-md-phd|Gregory F. Cooper]] (at the University of Pittsburgh). The areas of focus include: |
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| * development of Bayesian and information-theoretic methods for learning personalized models from clinical and genomic data, and | * development of Bayesian and information-theoretic methods for learning patient-specific models from clinical and genomic data, and |
| * application of personalized modeling to risk assessment, diagnosis, prognosis and selection of therapy. | * application of personalized modeling to risk assessment, diagnosis, prognosis and selection of therapy. |
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