Tool for Enhancing the Medical Professionals Capability for Pancreatic Cancer Risk Detection
From the cradle of medicine and throughout the development of medical art has been proved that the best treatment is the early,
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Developing Risk Prediction Models and evaluation of Interventions that can Delay / Early detect the Onset of Pancreatic Cancer
The pilot program of our partner Taipei Medical University (TMU) is to predict people at high risk for pancreatic and liver cancer
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Toxicity risk assessment in pancreatic cancer patients – a digital trial using iHelp framework
The iHelp project purpose is to develop a personalised healthcare framework that allows an early detection and mitigation of the risks associated
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The role of Karolinska Institutet in the iHelp project
The team from KI is led by Tanja Tomson, head of the Prevention, Policy and Practice (PPP) Unit at the Department of
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The Role of Enhanced Semantic Interoperability in the Healthcare Domain
Data have long been a critical asset for organizations, businesses, and governments and their analysis is of major importance for every stakeholder
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AI Support for Monitoring, Alerting, Feedback and Evaluation Module in iHelp
iHelp is part of the European Union’s Horizon 2020 Research and Innovation Program. The platform enables the collection, integration, and management of
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Tackling the complexity of Patient Oriented strategies
We are living in an age of intensive transformation. Ranging from industrial systems up to patient care in both acute or chronic
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The need for data integration in healthcare systems – the iHelp approach
The iHelp project aims at early identifying and mitigating the risks associated with Pancreatic Cancer by applying advanced AI-based learning and decision
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Database barriers in modern BigData healthcare applications
It has been a long discussion whether the use of traditional relational database management systems is valid for Big Data applications, where
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