TY - JOUR A1 - Munsch, Nicolas A1 - Gruarin, Stefanie A1 - Nateqi, Jama A1 - Lutz, Thomas A1 - Binder, Michael A1 - Aberle, Judith H. A1 - Martin, Alistair A1 - Knapp, Bernhard T1 - Symptoms associated with a COVID-19 infection among a non-hospitalized cohort in Vienna JF - Wiener Klinische Wochenschrift / The Central European Journal of Medicine N2 - Background: Most clinical studies report the symptoms experienced by those infected with coronavirus disease 2019 (COVID-19) via patients already hospitalized. Here we analyzed the symptoms experienced outside of a hospital setting. Methods: The Vienna Social Fund (FSW; Vienna, Austria), the Public Health Services of the City of Vienna (MA15) and the private company Symptoma collaborated to implement Vienna's official online COVID-19 symptom checker. Users answered 12 yes/no questions about symptoms to assess their risk for COVID-19. They could also specify their age and sex, and whether they had contact with someone who tested positive for COVID-19. Depending on the assessed risk of COVID-19 positivity, a SARS-CoV‑2 nucleic acid amplification test (NAAT) was performed. In this publication, we analyzed which factors (symptoms, sex or age) are associated with COVID-19 positivity. We also trained a classifier to correctly predict COVID-19 positivity from the collected data. Results: Between 2 November 2020 and 18 November 2021, 9133 people experiencing COVID-19-like symptoms were assessed as high risk by the chatbot and were subsequently tested by a NAAT. Symptoms significantly associated with a positive COVID-19 test were malaise, fatigue, headache, cough, fever, dysgeusia and hyposmia. Our classifier could successfully predict COVID-19 positivity with an area under the curve (AUC) of 0.74. Conclusion: This study provides reliable COVID-19 symptom statistics based on the general population verified by NAATs. Keywords: Chatbot; Machine learning; Self-reported; Symptom assessment; Symptom checker. KW - COVID-19 KW - Chatbot KW - Machine learning KW - Self-reported KW - Symptom assessment Y1 - VL - 2022 IS - 134 (9-10) SP - 344 EP - 350 PB - Springer ER - TY - JOUR A1 - Munsch, Nicolas A1 - Martin, Alistair A1 - Gruarin, Stefanie A1 - Nateqi, Jama A1 - Abdarahmane, Isselmou A1 - Weingartner-Ortner, Rafael A1 - Knapp, Bernhard T1 - Authors’ Reply to: Screening Tools: Their Intended Audiences and Purposes. Comment on “Diagnostic Accuracy of Web-Based COVID-19 Symptom Checkers: Comparison Study” JF - Journal of Medical Internet Research KW - COVID-19 KW - Symptom Checkers KW - Digital Health Y1 - IS - Vol 23, No 5 (2021) ER - TY - JOUR A1 - Groen-Xu, Moqi A1 - Boes, Gregor A1 - Teixeira, Pedro A. A1 - Voigt, Thomas A1 - Knapp, Bernhard T1 - Short-term Incentives of Research Evaluations: Evidence from the UK Research Excellence Framework JF - Research Policy KW - research funding systems KW - evaluation effects KW - economics of science KW - incentives KW - university Y1 - VL - Vol. 52 IS - Issue 6 ER - TY - GEN A1 - Knapp, Bernhard T1 - AI Engineering @ FHTW KW - Secure Services KW - eHealth & Mobility Y1 - ER - TY - GEN A1 - Knapp, Bernhard T1 - Keynote Lecture: Der Weg eines Bioinformatikers der ersten Stunde KW - Secure Services KW - eHealth & Mobility Y1 - ER - TY - GEN A1 - Knapp, Bernhard T1 - From academia to industry and back KW - Secure Services KW - eHealth & Mobility Y1 - ER - TY - GEN A1 - Knapp, Bernhard T1 - Ten simple rules for a successful cross-disciplinary collaboration N2 - Cross-disciplinary collaborations have become an increasingly important part of science. They are seen as key if we are to find solutions to pressing, global-scale societal challenges, including green technologies, sustainable food production, and drug development. The synergistic and skillful combining of different disciplines can achieve insight beyond current borders and thereby generate novel solutions to complex problems. The combination of methods and data from different fields can achieve more than the sum of the individual parts could do alone. Initiating and successfully maintaining cross-disciplinary collaborations can be challenging but highly rewarding. In this talk I will focus on the specific challenges associated with cross-disciplinary research, from the perspective of the theoretician in particular. Based on “10 simple rules” (https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004214) I will describe the key benefits, as well as some possible pitfalls, arising from collaborations between scientists with very different backgrounds. KW - Cross-disciplinary collaboration Y1 - ER - TY - JOUR A1 - Marc, Zobel A1 - Knapp, Bernhard A1 - Nateqi, Jama A1 - Martin, Alistair T1 - Correlating global trends in COVID-19 cases with online symptom checker self-assessments JF - PLOS ONE N2 - Background Online symptom checkers are digital health solutions that provide a differential diagnosis based on a user’s symptoms. During the coronavirus disease 2019 (COVID-19) pandemic, symptom checkers have become increasingly important due to physical distance constraints and reduced access to in-person medical consultations. Furthermore, various symptom checkers specialised in the assessment of COVID-19 infection have been produced. Objectives Assess the correlation between COVID-19 risk assessments from an online symptom checker and current trends in COVID-19 infections. Analyse whether those correlations are reflective of various country-wise quality of life measures. Lastly, determine whether the trends found in symptom checker assessments predict or lag relative to those of the COVID-19 infections. Materials and methods In this study, we compile the outcomes of COVID-19 risk assessments provided by the symptom checker Symptoma (www.symptoma.com) in 18 countries with suitably large user bases. We analyse this dataset’s spatial and temporal features compared to the number of newly confirmed COVID-19 cases published by the respective countries. Results We find an average correlation of 0.342 between the number of Symptoma users assessed to have a high risk of a COVID-19 infection and the official COVID-19 infection numbers. Further, we show a significant relationship between that correlation and the self-reported health of a country. Lastly, we find that the symptom checker is, on average, ahead (median +3 days) of the official infection numbers for most countries. Conclusion We show that online symptom checkers can capture the national-level trends in coronavirus infections. As such, they provide a valuable and unique information source in policymaking against pandemics, unrestricted by conventional resources. KW - Online symptom checkers KW - coronavirus disease Y1 - U6 - http://dx.doi.org/https://doi.org/10.1371/journal.pone.0281709 VL - 18 IS - 2 ER - TY - GEN A1 - Knapp, Bernhard T1 - ChatGPT 4.0 – friend or foe? KW - ChatGPT Y1 - ER - TY - GEN A1 - Knapp, Bernhard T1 - ChatGPT – Freund oder Feind? KW - ChatGPT Y1 - ER - TY - GEN A1 - Knapp, Bernhard T1 - ChatGPT – friend or foe? KW - ChatGPT Y1 - ER - TY - GEN A1 - Knapp, Bernhard T1 - ChatGPT – Freund oder Feind? KW - ChatGPT Y1 - 2024 ER - TY - GEN A1 - Knapp, Bernhard T1 - ChatGPT 4.0 – friend or foe? KW - ChatGPT Y1 - 2024 ER -