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    Clinical Decision Supporting System Development
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    Clinical Decision Supporting System

    A Semantic model-driven application with Natural Language Interfaces.

    Highlights

    Maria Skłodowska Curie Memorial Cancer Center and Institute of Oncology (MCMCC) based in Warsaw is a leader in cancer treatment in Poland. The best standards, advanced knowledge and experience in the treatment of the disease are concentrated there and the best doctors practice in the center. Unfortunately, other clinics in Poland do not have such high recovery rates, so we, together with the MCMCC, have developed a Clinical Decision Supporting System to systematize knowledge in oncology treatment and reduce the risk of medical error in all Polish oncology clinics. Besides, as it is compatible with OWL, a well known semantic web standard, and therefore it contributes to OWL community growth

    Industry

    Healthcare

    Science

    Team
    Duration

    months

    Country

    Poland

    Challenge

    It is necessary to have an open knowledge base on diagnosis and treatment that could be used by all specialized doctors in the country, regardless of their location and level of education.

    Decisions on the choice of one or another treatment pass through the line of diagnosis and treatment. Diagnosis includes all tests, x-rays, conversations with the patient and his medical history. Based on this, the doctor chooses one or another treatment that he considers appropriate in this particular case, taking into account the standards of treatment accepted in Europe. 

    But the experience of all doctors can be different and no one excludes the possibility of a medical error that can cost lives. Thus, our team was faced with the task of collecting and encoding all the data in one place (which is entered by doctors, laboratory assistants and other medical personnel) and combining it with a knowledge base accepted by ESMO (The European Society for Medical Oncology). The new solution was to analyze all the data, compare with the standards and help oncologists to give a conclusion.

    Solution

    For each individual patient, the system analyzes the data and gives a conclusion, but the final decision is always made by his doctor.

    From the technical side Clinical Decision Supporting System is a Semantic model-driven application with Natural Language Interfaces (CNL), simplified version of English. Based on the rules the app reasons out what is the next step of the therapy. Its medical guidelines are understood both by computer and human experts. The results can be exported to an OWL/XML file.

    We organized available data into the knowledge of the diagnostic process, based on many sources like studies, publications, recommendations, so it supports doctors decisions. We also developed a central registry for collecting patient’s clinical data from over 70 oncological institutions in Poland. The latter can help to identify patterns, get statistics and be the basis for further clinical research.

    Whitepaper

    Testimonials

    Cognitum rating opinions Cognitum rating opinions Cognitum rating opinions Cognitum rating opinions Cognitum rating opinions
    “I certify that Cognitum is as a highly skilled technology affiliate and specialists in their field.”
    We collaborated with Cognitum in the area of research for CDSS based on Semantic Web standards which is a new approach to deal with complex clinical information. Cognitum also supported COI with running Bone Cancer Registry. I certify that Cognitum is as a highly skilled technology affiliate and specialists in their field.

    Iwona Ługowska

    Professor, Maria Skłodowska-Curie Institute of Oncology

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    Technology Specification

    Cognitum Software House C#
    Cognitum Software House Javascript
    Cognitum Software House ASP.NET
    Cognitum Software House CogniPy

    frontend:

    Javascript, Bootstrap

    backend:

    ASP.NET, C#, CogniPy

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