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The Ambrose Monell Fellowship at Cleveland Clinic suggests, importantly, that the successful fellow will understand how to form hypotheses from clinical observations and to design experiments to effectively answer the hypothesis. In essence, this appears to be the near universal role of clinical genetics, working from the clinical to the laboratory.
Arguably, the opposite might yield greater diagnostic accuracy and efficacy by correlating the genomic profile back to the signs, symptoms and anthropomorphic data of the patient. Testing for only suspected abnormalities to confirm a diagnosis, removes the chance for finding a missed diagnosis, questioning a wrong diagnosis or establishing an individual patient database from which future information might be derived.
I'm looking for a place where I can link the patient history with an inexpensive, less than $100 US, genomic profile and apply statistical analysis to the associations -- translational medicine. The predictive accuracy will build over time, but it will not build until you have the data and the data must be personal or highly regional. The data must apply to the patient or patients in question. A national database fails in that regard. A clinician who keeps good records and for the life of his or her practice, will have a database of some fifty thousand records. These numbers may be adequate for good data mining, but your patient is a statistic of N=1.
Arguably, the opposite might yield greater diagnostic accuracy and efficacy by correlating the genomic profile back to the signs, symptoms and anthropomorphic data of the patient. Testing for only suspected abnormalities to confirm a diagnosis, removes the chance for finding a missed diagnosis, questioning a wrong diagnosis or establishing an individual patient database from which future information might be derived.
I'm looking for a place where I can link the patient history with an inexpensive, less than $100 US, genomic profile and apply statistical analysis to the associations -- translational medicine. The predictive accuracy will build over time, but it will not build until you have the data and the data must be personal or highly regional. The data must apply to the patient or patients in question. A national database fails in that regard. A clinician who keeps good records and for the life of his or her practice, will have a database of some fifty thousand records. These numbers may be adequate for good data mining, but your patient is a statistic of N=1.
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