mineRARE: Semantic text-mining of electronic medical records as diagnostic decision support tool to search for rare neurologic diseases such as Pompe disease, Fabry disease and Niemann-Pick type C disease

Abstract

Background and aims:Diagnosis of rare neurogenetic disorders is often challenging, particularly adult-onset presentations, with long diagnostic delays and misdiagnosis. As therapies become available, it is increasingly important to identify patients with rare neurologic diseases.

Methods:This multicenter project on ten rare neurogenetic diseases was approved by local Ethics committees and data protection authorities of six German University medical centers. Semantic text mining software structures medical data by ranking documents according to probability of disease, based on disease-specific lists of weighted signs and symptoms. Software and search algorithms were optimised in a pilot phase. Existing electronic medical records from the Department of Neurology of each center, corresponding to 10 years of activity, were screened, and patients ranked by probability of having the respective disease. An experienced team of physicians reviewed the data for the top ranked patients and those without a confirmed diagnosis were contacted for testing for the respective disease.

Results:In the pilot phase, 4 patients with Pompe disease and 4 heterozygous NPC1 mutation carriers were identified in Munich. More than 400.000 datasets from four centers were analysed for three diseases: Niemann-Pick type C disease, Pompe disease and Fabry disease. Four novel Pompe patients and 3 heterozygous NPC1or NPC2 mutation carriers were identified, who had not previously been diagnosed. Data from more centers will be provided.

Conclusion:Electronic medical records-based diagnostic data mining seems to be a promising tool to help diagnosing rare neurologic diseases. It may allow effective screening, re-evaluation of patients with uncertain diagnosis, and identification of patients for clinical trials.

Disclosure:
This research was supported by research grants from Sanofi Genzyme and Actelion.

Cite this article as:

Catarino C, Grandjean A, Doss S, Mücke M, Tunc S, Schmidt K, Schmidt J, Young P, Bäumer T, Kornblum C, Endres M, Daumke P, Klopstock T, Schoser B. mineRARE: Semantic text-mining of electronic medical records as diagnostic decision support tool to search for rare neurologic diseases such as Pompe disease, Fabry disease and Niemann-Pick type C disease. European Journal of Neurology 07/2017; 24(Suppl 1):75-75.

Philipp Daumke
Philipp Daumke
Dr. Philipp Daumke is responsible for the strategic development of the company, product planning and marketing. He received a MD from the University Hospital of Freiburg and as a doctor he is able to incorporate his biomedical expertise into the company. In addition, as a computer scientist and due to his developmental work, he possesses excellent know-how of the Averbis products. Various publications and awards reflect his many years of scientific experience in the field of the analysis of unstructured data.

Jetzt weitere Informationen und Demo anfordern!

kostenlos & unverbindlich

Anwendungsgebiet
HealthcarePatentePharmaAndere

Vorname (Pflichtfeld)

Name (Pflichtfeld)

Jobtitle / Rolle (Pflichtfeld)

Firma (Pflichtfeld)

E-Mail-Adresse (Pflichtfeld)

Telefon

Nachricht


Get more Information or schedule a FREE Demo

Use case
HealthcarePatentsPharmaOthers

First Name (required)

Last Name (required)

Job Title / Role (required)

Company (required)

Email (required)

Phone

Message