predictive analytics
background

Predictive analytics is one of the most promising data science techniques that can be applied in healthcare domain. The underlyig idea is to use the knowledge from EMR/EHR data sets for predictio of what will happen to a patient or a group of patients in future.

business challenges

It was asked to estimate the treatment outcome for a given patient before the actual presciprtion and thus to select the most efficient treatment path.


value delivered

We've successfully developed a set of rules base on various criteria, such as age, gender, previous diseases etc. helipng medical professionals provide a personalized treatment flow for each patient.


approach

To fulfil the task, we have split all patient-level data (EMR/EHR) into separate classes based on the treatment outcome for particular diseases (positive, negative, no progress). The next step was to run 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.


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our expertise in

AI technologies

data mining

PCA
K-means
Decision trees
Linear models
PageRank

digital signal processing

Digital filters
DTW

machine learning

Deep learning
Probabilistic graphical models
CART
ensembles
unsupervised sound segmentation
recurrent models
bayesian approach
probabilistic programming
hmm

image processing and
computer vision

alexnet
vgg
vae

natural language
processing

PCA
TF-IDF
LDA
SVM
Naive bayes
word2vec
attention models

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about us

Hi, we are Sciforce - a company where the integration of various branches of science builds up a powerful force to create robust software solutions. Working at the intersection of Computer Science with other technical, natural and humanitarian sciences let us go beyond traditional IT services and become both technical and scientific forces to our customers.