PCA, Linear models, Deep learning, Probabilistic graphical models, Naive bayes
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One of the most future-oriented data science technologies applied in healthcare segment. The fundamental idea is to use the knowledge from EMR/EHR data for prediction of what will happen to a patient or a group of patients in future.
Estimate the treatment outcome for a certain patient before the actual prescription and thus to select the most efficient treatment way.
To split all patient-level data (EMR/EHR) into separate classes based on the treatment outcome for particular diseases (positive, negative, no progress). The next stage implies running an advanced machine learning algorithm over the data and to train a model that would be able to predict a treatment outcome. The given model can be used for further predictions.
Creation of a set of rules based on different data, such as age, gender, previous diseases, etc. helping medical professionals provide an individual treatment for each patient.
Our latest challenges where technology meets creativity
The technique to identify unusual patterns that do not conform to expected behavior
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