1

Developing Methods and Algorithms to Determine a Geo Distribution of Cancer

Healthcare
Data-Driven Analytics

Description

The National Scientific and Practical Children’s Center of Oncology and Hematology asked to develop methods and algorithms as well as a software system that would build and visualize clusters representing the geographical distribution of cancer incidence.

The customer

The customer is the National Scientific and Practical Children’s Center of Oncology and Hematology that provides treatment to children of up to 18 years of age with all types of hematological and oncological pathologies (except for thyroid gland cancer), as well as in-born immune deficiencies. The Center performs transplantation of peripheral stem cells, mesenchymal cells, and umbilical cord blood cells as well as marrow-bone transplantation. Medical services are provided by highly skilled experts, including five Ph.D.’s of Medical Sciences and 16 Candidates of Sciences.

The need

Malignant tumors in children are a complex social and economic problem as the cost of therapy for tumors and the death rates are very high. Despite significant achievements in treatment, this type of disease is one of the leading causes of death for children in the world and in Belarus. Taking into account the fact that malignant tumors in children are relatively rare, standard epidemiological methods do not work. In order to determine relations between cause and effect and improve the efficiency of preventive measures, we need a large sample of cases.

Over the last decade, dimensional and dimensional-temporal methods of cluster analysis became widely spread in research of geographical distribution of various types of disease. These methods are designed to determine and build clusters of communities with increased incidence of diseases. The task was to develop methods and algorithms as well as a software system that would build and visualize clusters representing the geographical distribution of cancer incidence in children and teenagers living in Belarus.

The solution

We developed statistical criteria for global clustering to determine, if there is any clustering of disease incidence on the territory under consideration.

We also created methods and algorithms for local clustering that make it possible to build clusters representing geographical distribution of increased incidence of disease during a particular period of time.

Finally, we built a software system for building and visualizing clusters that represent incidence of cancer.

The outcome

The software system developed by our institute made it possible to single out clusters of regions and communities with increased incidence of leukemia, carcinoma, and other malignant tumors. If we can determine the regions and communities with the highest risk of cancer, this information can be used for early diagnosis of this type of diseases. Thus, we can save the lives of many children.

You May Also Like

Automation of In-field Job Planning and Performance Optimization
Java
JavaScript
PostgreSQL
Information technology
Marketing
Call Recording, Analytics, and Workforce Optimization Solution
.NET
jQuery
C#
JavaScript
MS SQL
Information technology
Highly Scalable System for DNA Analysis
Hadoop
Java
Information technology
Healthcare
Sport
A Highly Secure Smart Home System Wins a Kickstarter Funding
Ruby
Ruby on Rails
JavaScript
Angular
PostgreSQL
MySQL
Information technology
The Image Recognition System
Java
MongoDB
NoSQL
e-Commerce
Integrated logistics solutions to the offshore industry
Android
LikeFolio: Best Practices of Cloud and Ruby Development for Application Optimization
NoSQL
MySQL
Ruby
Ruby on Rails
Marketing
Social media
Telecommunications
Finance
Data-Driven Analytics
Software for Selecting and Mixing Paint
.NET
MS SQL
C#
WP
Information technology
Retail
Software Suite for Mobile Technicians and Field Service Management
.NET
MS SQL
iOS
Android
Logistics and transportation
The System for Emergency Control Centers
.NET
C#
MS SQL
Healthcare
Sport
Logistics and transportation
The Cloud-based Document Exchange System
Java
jQuery
NoSQL
Information technology
e-Commerce
The Marketing Information Messaging System
.NET
C#
MS SQL
iOS
Marketing, Social media
Telecommunications
The NuoDB Migrator for Moving SQL Data to a NoSQL Database
Java
NuoDB
MySQL
PostgreSQL
Information technology
Manufacturing
Toyota Automates Its System for Holding Tenders
.NET
C#
Manufacturing
Warehouse Workload Monitoring Application
.NET
C#
MS SQL
WP
Logistics and transportation
Web-Based Personal Styling
Ruby
Ruby on Rails
JavaScript
jQuery
MySQL
Social media
e-Commerce
Web-Based System for Retailers
Ruby
Ruby on Rails
MySQL
MongoDB
Retail
e-Commerce
A Blockchain-Based Platform for Automating Bond Issuing Worth $10M
Bash
JavaScript
Blockchain
Finance

Contact us

Jan-Terje Nordlien

Daglig leder

jan-terje@altoros.no+47 21 92 93 00

Altoros Norge AS
Org.nr.: 894 684 992
Tordenskiolds gate 2,
0160 Oslo