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Symptoma, Better Diagnosis for Patients with Rare and Complex Diseases

CORDIS bietet Links zu öffentlichen Ergebnissen und Veröffentlichungen von HORIZONT-Projekten.

Links zu Ergebnissen und Veröffentlichungen von RP7-Projekten sowie Links zu einigen Typen spezifischer Ergebnisse wie Datensätzen und Software werden dynamisch von OpenAIRE abgerufen.

Leistungen

D3.1 Spanish, Japanese, and Arabic version of Symptoma released.

D3.1 Spanish, Japanese, and Arabic version of Symptoma released.T3.1 Pre-translation engine: translating our ontology in the respective language via machine translation (aggregating results of Google, Bing, Yandex, and Deepl) and medical databases such as Orpha.net, Wikipedia, and the International Classification of Diseases.T3.2 Review process: carried out redundantly by native-speaking medical professionals. We will provide a platform to review each pre-translation within the context of the original concept. T3.3 Data mining: articles from Pubmed, eBooks, journals, and the Web for each language version. For each translation analyzing whether those phrases are being used in context of the associated concepts (e.g. are the right symptoms mentioned alongside the suggested disease name?).T3.4 Localization: of Symptoma to Spanish, Japanese, and Arabic using our new localization engine.

D2.2 Release question sequences derived from deep learning algorithms.

D2.2 Release question sequences derived from deep learning algorithms. T2.2 Train chatbot: utilizing the same case reports as in WP1. However, instead of searching with all symptoms extracted from the respective case, we start with one symptom only. Deep learning algorithms will then arrive at the best question sequence uncovering the other symptoms thus leading to the right diagnosis. Question sequences should then work for all 44,000 conditions in our database while accounting for disease incidences (a more common disease should have a higher priority than a rare one).T2.3 Test chatbot: in production. As in WP1, we will release question sequences to production, monitor search signals indicating successful questions, and continuously optimize for it.

Veröffentlichungen

Predicting Global Trends in COVID-19 Cases Via Online Symptom Checkers Self-Assessments

Autoren: Marc Zobel, Alistair Martin, Jama Nateqi, Bernhard Knapp
Veröffentlicht in: SSRN Electronic Journal, 2020, ISSN 1556-5068
Herausgeber: SSRN
DOI: 10.2139/ssrn.3729913

Querdenker-Preis

Autoren: DGIM
Veröffentlicht in: DMW - Deutsche Medizinische Wochenschrift, Ausgabe 144/15, 2019, Seite(n) 1085-1085, ISSN 0012-0472
Herausgeber: Georg Thieme Verlag
DOI: 10.1055/a-0954-8989

Global review of assisted diagnosis tools using medical database and artificial intelligence methods to improve complex disease diagnosis

Autoren: Anne Blériot, Franck Le Meur, Guillaume De Chamisso
Veröffentlicht in: Research Square, 2021, ISSN 2693-5015
Herausgeber: Research Square
DOI: 10.21203/rs.3.rs-157785/v1

An artificial intelligence-based first-line defence against COVID-19: digitally screening citizens for risks via a chatbot

Autoren: Alistair Martin, Jama Nateqi, Stefanie Gruarin, Nicolas Munsch, Isselmou Abdarahmane, Marc Zobel, Bernhard Knapp
Veröffentlicht in: Scientific Reports, Ausgabe 10/1, 2020, ISSN 2045-2322
Herausgeber: Nature Publishing Group
DOI: 10.1038/s41598-020-75912-x

Diagnostic Accuracy of Web-Based COVID-19 Symptom Checkers: Comparison Study

Autoren: Nicolas Munsch, Alistair Martin, Stefanie Gruarin, Jama Nateqi, Isselmou Abdarahmane, Rafael Weingartner-Ortner, Bernhard Knapp
Veröffentlicht in: Journal of Medical Internet Research, Ausgabe 22/10, 2020, Seite(n) e21299, ISSN 1438-8871
Herausgeber: Journal of medical Internet Research
DOI: 10.2196/21299

Vom Symptom zur Diagnose – Tauglichkeit von Symptom-Checkern

Autoren: J. Nateqi, S. Lin, H. Krobath, S. Gruarin, T. Lutz, T. Dvorak, A. Gruschina, R. Ortner
Veröffentlicht in: HNO, Ausgabe 67/5, 2019, Seite(n) 334-342, ISSN 0017-6192
Herausgeber: Springer Verlag
DOI: 10.1007/s00106-019-0666-y

COVID-19 symptom frequency comparison: non-hospitalised positively and negatively tested persons with flu-like symptoms in Austria

Autoren: Nicolas Musch, Stefanie Gruarin, Alistair Martin, Jama Nateqi, Thomas Lutz, Judith H. Aberle, Bernhard Knapp
Veröffentlicht in: medRxiv, 2021
Herausgeber: medRxiv
DOI: 10.1101/2021.02.24.21252426

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