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Personalized Treatment Prediction

Published: September 29, 2022
# Healthcare
# Data Science
Since the time of Hippocrates clinicians all over the world strive to cure the patient, not the illness. Since a human is a highly organized creature with its features, everyone develops the disease and reacts to medical treatment differently. One of our clients decided to develop a treatment prediction solution based on personalized EHR/EMR data. Check out how our experienced team contributed to this project!

Challenge

“One-size-fits-all” approach to treatment, based on a broad population average, is not taking into account age, gender, lifestyle, previous diseases, comorbidities, or genetics. That is why it can be challenging to select an optimal treatment schema for all cases. But applying personalized EHR/EMR data and predictive ML can ensure personalized treatment, so our team decided to create a method for treatment outcome prediction.

Solution

  • All patient-level data (EMR/EHR) received from our clients was transformed into standardized machine-readable format. Later we defined cohorts, i.e., separate classes based on the treatment outcome for particular diseases (“positive”, “negative”, and “no progress”).
  • The next step was to create and run a machine learning algorithm over the data and to train a model that would be able to predict a treatment outcome.
  • We consider the given model to be used for further predictions.

Development Journey

  1. Domain Expertise in Healthcare
  2. Natural Language Processing (NLP)
  3. Relational Database Management (SQL-based)
  4. ETL process: OHDSI Software Tools (Whiterabbit and Rabbit-in-a-hat, Usagi, Athena, Achilles, Atlasi)
  5. Data Science and Data Analytics
  6. Programming languages: R, Python, SQL
  7. Machine Learning
  8. Predictive Analysis

Impact

Having processed a great amount of patient data, we can formulate a treatment strategy based on various criteria, such as age, gender, medical history and genetic profile. So this is how we are helping doctors to provide a personalized therapeutic treatment plan for each patient.

We believe that these actions bring us closer to the bright future where the individual approach in fighting the disease will be easier, cheaper and as a result much more efficient.

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