Method for stratifying ibs patients
A patient-algorithmic technology applied to patient-specific data, neural learning methods, data from laboratory analysis, etc.
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[0075] Described herein are methods and systems that enable accurate stratification of IBS patients from their microbiomes, particularly where the patient's microbiome is similar to the average microbiome of a person without IBS. Previously, it was a challenge to distinguish this specific subgroup of IBS patients from those with altered microbiomes.
[0076] Furthermore, diagnosing IBS from a patient's microbiome can lead to a more informed diagnosis than from patient-reported symptoms alone, where the latter can lead to variable and inaccurate results and inappropriate treatment strategies. Therefore, it would be advantageous to be able to diagnose a patient's IBS from the patient's microbiome. Additionally, methods and systems are described herein that can be used to generate a trained classifier for performing IBS diagnoses. A trained classifier can be stored for execution by the processor using the microbiome data of the test sample to provide an output indicative of the ...
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Abstract
Description
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Application Information
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