DIESEL-X: A Game-Based Tool for Early Risk Detection of Dyslexia in Preschoolers

2015 ◽  
pp. 93-114 ◽  
Author(s):  
Luc Geurts ◽  
Vero Vanden Abeele ◽  
Véronique Celis ◽  
Jelle Husson ◽  
Lieven Van den Audenaeren ◽  
...  
Keyword(s):  
Risk Detection ◽  
Early Risk

scholarly journals HeartCare+: A Smart Heart Care Mobile Application for Framingham-Based Early Risk Prediction of Hard Coronary Heart Diseases in Middle East

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Hoda Ahmed Galal Elsayed ◽  
Mariam Ahmed Galal ◽  
Liyakathunisa Syed
Keyword(s):  
Middle East ◽  
Mobile Technology ◽  
Rural Areas ◽  
Heart Diseases ◽  
Mobile App ◽  
High Rate ◽  
Cardiac Diseases ◽  
Coronary Heart Diseases ◽  
Risk Detection ◽  
Early Risk

Background. Healthcare is a challenging, yet so demanding sector that developing countries are paying more attention to recently. Statistics show that rural areas are expected to develop a high rate of heart diseases, which is a leading cause of sudden mortality, in the future. Thus, providing solutions that can assist rural people in detecting the cardiac risks early will be vital for uncovering and even preventing the long-term complications of cardiac diseases. Methodology. Mobile technology can be effectively utilized to limit the cardiac diseases’ prevalence in rural Middle East. This paper proposes a smart mobile solution for early risk detection of hard coronary heart diseases that uses the Framingham scoring model. Results. Smart HeartCare+ mobile app estimates accurately coronary heart diseases’ risk over 10 years based on clinical and nonclinical data and classifies the patient risk to low, moderate, or high. HeartCare+ also directs the patients to further treatment recommendations. Conclusion. This work attempts to investigate the effectiveness of the mobile technology in the early risk detection of coronary heart diseases. HeartCare+ app intensifies the communication channel between the lab workers and patients residing in rural areas and cardiologists and specialist residing in urban places.

Impact of prenatal exposure characterization on early risk detection: Methodologic insights for the HEALthy Brain and Child Development (HBCD) study

2021 ◽  
pp. 107035
Author(s):  
Suena H. Massey ◽  
Norrina B. Allen ◽  
Lindsay Pool ◽  
Emily S. Miller ◽  
Nicole R. Pouppirt ◽  
...  
Keyword(s):  
Child Development ◽  
Prenatal Exposure ◽  
Risk Detection ◽  
Early Risk

Unerwartete Unternehmensinsolvenz trotz testiertem Risikomanagement? – Lessons Learned aus der Insolvenz der Gerry Weber International AG

2020 ◽  
Vol 61 (3) ◽  
pp. 139-154
Author(s):  
Werner Gleißner ◽  
Kay H. Hofmann
Keyword(s):  
Annual Report ◽  
Detection System ◽  
Lessons Learned ◽  
Legal Requirements ◽  
External Auditors ◽  
Detection Systems ◽  
Risk Detection ◽  
Early Risk ◽  
Management Procedures ◽  
Risk Aggregation

Summary Studies show that the implemented and certified early risk detection systems in practice are often unable to identify developments that could jeopardize a company’s existence. This is due to methodological weaknesses, e.g. insufficient consideration of the liquidity effect of risks, the lack of analysis of extreme risks and, in particular, the absence of adequate risk aggregation that considers interdependencies and hence combination effects of risks. In many recent insolvencies, among them the here investigated case of Gerry Weber International AG, it is easy to see that the early risk detection system, as explained in the Annual Report, has not fulfilled the legal requirements. In order to avoid such „unexpected insolvencies“, it is necessary to implement advanced risk management procedures and pursue audits that are more rigorous. The article at hand develops a concise but comprehensive assessment scheme that may not only be easily applied within companies but also by external auditors. Zusammenfassung Die meisten börsennotierten Gesellschaften haben ein Risikofrüherkennungssystem, das vom Abschlussprüfer ohne den Verweis auf schwerwiegende Mängel testiert wird. Tatsächlich zeigen Studien, dass die in der Praxis implementierten Systeme häufig ungeeignet sind, um an sich erkennbare bestandsgefährdende Entwicklungen zu identifizieren. Dies liegt an methodischen Schwächen, z. B. an einer fehlenden Betrachtung der Liquiditätswirkung von Risiken, einer vernachlässigten Analyse von Extremrisiken und insb. am Fehlen einer Risikoaggregation, die auch Kombinationseffekte berücksichtigt. Bei Insolvenzen, wie hier im Beispiel von Gerry Weber, lässt sich bei Betrachtung des dokumentierten Risikomanagementsystems erkennen, dass die gesetzlichen Anforderungen nicht erfüllt wurden. Um solche „überraschenden Insolvenzen“ zu vermeiden, ist es erforderlich, bessere Verfahren zu implementieren und durch Prüfer testieren zu lassen, was bisher nicht konsequent geschieht. Der Beitrag schlägt ein einfaches aber umfassendes Prüfschema für Risikofrüherkennungssysteme vor, das sowohl intern als auch von externen Prüfern verwendet werden kann.

scholarly journals τ-SS3: A text classifier with dynamic n-grams for early risk detection over text streams

2020 ◽  
Vol 138 ◽  
pp. 130-137
Author(s):  
Sergio G. Burdisso ◽  
Marcelo Errecalde ◽  
Manuel Montes-y-Gómez
Keyword(s):  
Risk Detection ◽  
Early Risk ◽  
Text Streams

scholarly journals Early Risk Detection of Burnout: Development of the Burnout Prevention Questionnaire for Coaches

2019 ◽  
Vol 10 ◽  
Author(s):  
Paul Schaffran ◽  
Jens Kleinert ◽  
Sebastian Altfeld ◽  
Christian Zepp ◽  
Konrad Wolfgang Kallus ◽  
...  
Keyword(s):  
Burnout Prevention ◽  
Risk Detection ◽  
Early Risk

scholarly journals Commentary: Early Risk Detection of Burnout: Development of the Burnout Prevention Questionnaire for Coaches

2019 ◽  
Vol 10 ◽  
Author(s):  
Erik Lundkvist ◽  
Henrik Gustafsson ◽  
Markus Gerber ◽  
Carolina Lundqvist ◽  
Andreas Ivarsson ◽  
...  
Keyword(s):  
Burnout Prevention ◽  
Risk Detection ◽  
Early Risk

scholarly journals Response: Commentary: Early Risk Detection of Burnout: Development of the Burnout Prevention Questionnaire for Coaches

2020 ◽  
Vol 11 ◽  
Author(s):  
Paul Schaffran ◽  
Jens Kleinert ◽  
Sebastian Altfeld ◽  
Christian Zepp ◽  
Konrad Wolfgang Kallus ◽  
...  
Keyword(s):  
Burnout Prevention ◽  
Risk Detection ◽  
Early Risk
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