 https://bengreenfieldfitness.com/machinelearning

I recently took a test that uses machine learning to predict biochemical test results (like blood, urine and stool) - a test called the "Elite Performance Analysis (EPA) tool". Over the last three years, the folks at Nourish Balance Thrive (Dr. Tommy Wood and Chris Kelly, both former podcast guests) who designed this test have worked with over 1,000 athletes, averaging over 100 biochemical markers collected per athlete, including: -Blood biochemistry-Urine tests (DUTCH and organic acids)-Stool tests (PCR and culture)-Subjective quality of life questions (a Health Assessment Questionnaire, or HAQ), scored on an analog scale (1-5) As well as working to optimize the performance of athletes at every level, another goal of Nourish Balance Thrive is to give more people access to the type of work they do by increasing speed of access and reducing cost. Machine learning provides for a very good way to do this. By training an algorithm based on historical HAQ and biochemical test data, they can predict five common patterns of performance killers that they regularly see in their clients, including: 1. Blood sugar dysregulation (high/low fasting blood sugar and HbA1c, or high fasting insulin)2. Low sex hormones (testosterone in men and oestrogen in women)3. Suboptimal hemoglobin (“low oxygen deliverability”

https://bengreenfieldfitness.com/machinelearning I recently took a test that uses machine learning to predict biochemical test results (like blood, urine and stool) - a test called the "<a href="https://bengreenfieldfitness.com/nourishbalancethrive" target="_blank" rel="noopener">Elite Performance Analysis (EPA) tool</a>". Over the last three years, the folks at Nourish Balance Thrive (Dr. Tommy Wood and Chris Kelly, both former podcast guests) who designed this test have worked with over 1,000 athletes, averaging over 100 biochemical markers collected per athlete, including: -Blood biochemistry -Urine tests (DUTCH and organic acids) -Stool tests (PCR and culture) -Subjective quality of life questions (a Health Assessment Questionnaire, or HAQ), scored on an analog scale (1-5) As well as working to optimize the performance of athletes at every level, another goal of Nourish Balance Thrive is to give more people access to the type of work they do by increasing speed of access and reducing cost. Machine learning provides for a very good way to do this. By training an algorithm based on historical HAQ and biochemical test data, they can predict five common patterns of performance killers that they regularly see in their clients, including: 1. Blood sugar dysregulation (high/low fasting blood sugar and HbA1c, or high fasting insulin) 2. Low sex hormones (testosterone in men and oestrogen in women) 3. Suboptimal hemoglobin (“low oxygen deliverability”

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https://bengreenfieldfitness.com/machinelearning I recently took a test that uses machine learning to predict biochemical test results (like blood, urine and stool) - a test called the "". Over the last three years, the folks at Nourish Balance Thrive...

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