Predictive Modelling
background

Predictive modelling is a process that uses data mining and probability to forecast outcomes. Each model is made up of a number of predictors, which are variables that are likely to influence future results. Once data has been collected for relevant predictors, a statistical model is formulated.

business challenges

We got order to predict the risk of a disease progression (e.g relapse, protracted clinical course) for patients with lung cancer and lymphoma.


value delivered

Required cohorts were defined after transforming raw data to CDM model. Based on it, we provided stable statistical models to the customer, which predicted outcomes, using data collected for patient during "time at risk" window.


approach

Our team developed universal step-by-step method, that included:

  • 1. Conversion of scattered medical definitions to strict machine-readable language.
  • 2. Implementing of deep machine learning technologies (GBM, Lasso Logistic regression, Neural networks, etc.)
  • 3. Visualization of obtained models to human-readable format for medical community.


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Case Studies

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  • Cohort Definition
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  • Medical Terminology
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our expertise in

Health IT Technologies

Data Analytics

Big Data Science
ETL
MapReduce
Hadoop

Data Warehouses

Relational Data Bases
SQL Server
Redshift

Hardware and Infrastructure

Cloud Computing
DevOps
AWS EC2
AWS S3

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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.