Fuzzy Cognitive Explainable Analytics for Translating Model Complexity in Nuclear Medical Diagnosis (EMERALD)
Explainable Artificial Intelligence in Nuclear Medicine
EMERALD takes a unique, holistic approach to patient-specific predictive modeling and MDSS development by extracting and integrating knowledge from new research, clinical tests and EHR using advanced analytic techniques
About the Project
Explore the project's concepts and implementation methods
Collaborators
Meet the collaborators of the project, as well as the involved Institutions
Results
The project's accomplishments and its contribution to Nuclear Medicine
EMERALD deals with two major challenges in Nuclear Medicine
EMERALD's focal point is Coronary Artery Disease and Non-Small Cell Lung Cancer
Coronary Artery Disease
Cardiovascular Diseases (CVD) remain fatal diseases across the world, whilst the early and non-invasive detection and prognosis is still an open issue. CDVs are the leading cause of death in the EU.
Non-Small Cell Lung Cancer
NSCLC constitutes the major cause of cancer deaths worldwide in both men and women accounting for approximately 85% of the total lung cancers
The EMERALD Project receives funding from the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the “2nd Call for H.F.R.I. Research Projects to support Faculty Members & Researchers” (Project Number: 3656) ELIDEK.
