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Predictive Medicine Powered by Artificial Intelligence

Predictive Medicine Powered by Artificial Intelligence

Using advances in technology to support clinical decision making

By combining in-depth expertise in medical biology with advanced computer technology, Biron offers health care professionals clinical decision support aimed at predicting health problems that are often unsuspected. Based on routine blood tests, these predictions will assist them in considering complementary analyses if they are deemed clinically relevant.

Did you know?

Innovations in artificial intelligence are now being taken very seriously or are already in use among various medical specializations. In addition to radiology and pathology, these include oncology, dermatology, ophthalmology and much more. [1] While this list is quickly growing, what is happening with laboratory medicine?

A publication from Harvard Medical School demonstrated that it is possible to accurately differentiate between normal and abnormal ferritin levels without directly measuring them. This achievement was possible thanks to a mathematical and statistical approach whereby a computer processes an enormous amount of information, including demographic, biochemical and hematological data from patients. It can also improve its own problem-solving performance (also known as machine learning). In addition, the study found that ferritin levels predicted by artificial intelligence may in certain cases better reflect the patient’s actual iron status than by measuring ferritin directly.

Prediction process

Process applied to the prediction of Ferritin levels

4 possible scenarios:

  1. Ferritin level is predicted to be abnormally low when iron deficiency is not suspected. Consider a ferritin test if clinically relevant.
  2. Ferritin level is predicted to be abnormally high when iron overload is not suspected. Consider a ferritin test if clinically relevant.
  3. Ferritin level is predicted to be significantly different from the measured ferritin. e.g. normalization of ferritin levels due to a mixed status (inflammation masks an underlying iron deficiency).Consider prediction if clinically relevant.
  4. No abnormalities are predicted.
Process applied to the prediction of HbA1c

2 possible scenarios:

  1. Identification of an elevated glycated hemoglobin (greater than or equal to 5.5%) when a metabolic disorder is not suspected.
  2. No abnormalities are predicted.
Process applied to the prediction of PTH

2 possible scenarios:

  1. Identification of an elevated PTH, while hyperparathyroidism is not suspected.
  2. No abnormalities are predicted.

What should be done in case of an abnormal ferritin prediction?

For ferritin, TWO options are available to the requesting physician:
  1. Biron may analyze the patient’s ferritin, free of charge*, based on the sample used for the initial blood test.
    Contact Biron - Direct line for health care professionals: 1-866-923-9222 ext. 2846
  2. Prescribe a ferritin test for the patient, with a new sample.

*Subject to change

For PTH or HbA1c, ONE option is available to the requesting physician:
  1. Prescribe the dosage of PTH or HbA1c to the patient from a new sample, free of charge*.

*Subject to change

Important considerations for health care professionals

  • Under no circumstances will the measurement of the abnormal predicted analyte be performed as a reflex. The decision to act on a prediction is entirely up to the clinician.
  • Patients do not have access to the predictions.
  • Predicting ferritin is just the beginning for Biron. More algorithms for the early detection of health problems will follow.
Sources1
  1. CADTH. An Overview of Clinical Applications of Artificial Intelligence. CADTH, Ottawa; 2018 (CADTH issues in emerging health technologies; issue 174).

FAQ

Where does the data used by the algorithm come from?

How long is the data used retained?

Do you have the right to use your patients' medical information?

How do you ensure that this data is secure?

Do you sell this data?

Did you ask your patients for consent before using their medical data?

If a Biron patient does not want their medical data to be used in yours algorithms, how can they ensure that it is not?

Will the patient have access to this predictive data?

Will the predictive data section appear on all Biron reports?

Why did you choose ferritin?

Why did you choose HbA1c?

Why did you choose PTH?

Do you plan to release other predictive data?