Clarify
CLoud ARtificial Intelligence For pathologY
Samarbeidspartnere
University of Amsterdam, Erasmus University Medical Center in Rotterdam, University of Granada, Politechnical University of Valencia, University Hospital Valencia, University of Stavanger.
Formål
CLARIFY is an innovative, multinational, multi-sectorial, and multidisciplinary research and training programme that links two highly differentiated specialities: engineering and medicine, to produce 12 Early Stage Researchers (ESRs) in artificial intelligence (AI), cloud computing and clinical pathology with the focus on digital pathology.
CLARIFY’s main goal is to develop a robust automated digital diagnostic environment based on artificial intelligence and cloud-oriented data algorithms that facilitates whole-slide-image (WSI) interpretation and diagnosis everywhere with the aim of maximising the benefits of digital pathology and aiding pathologists in their daily work.
CLARIFY gathers relevant scientific staff from academia, industry and leading hospitals ensuring that CLARIFY’s ESRs, as well as, future PhD students following the same tracks, will have outstanding Career Opportunities within the digital pathology sector and beyond.
Specific and challenging cancer types have been selected to test the tools and methods developed through the project reflecting the existing variability in cancer diagnosis: Triple negative breast cancer (TNBC), High-risk non-muscle invasive bladder cancer (HR-NMIBC) and Spitzoid melanocytic lesions (SML).
Problemstilling
The current pathology routine diagnosis is either not precise enough or/and not reproducible enough. Therefore under- and overtreatment of cancer patients still is a huge problem.
Ekstern lenke til prosjektet
Pågående prosjekt
Prosjektperiode
2019 - 2023
Kategorier
Fokusområde:
Klinisk, IKT-infrastruktur/datatilgang, Kompetanseutvikling
Type helsetjeneste:
Spesialist
Type data:
Bilder, Strukturerte data
Datakilde:
Annet
Planlagt sluttfase:
Testing og validering
Oppgave:
Diagnostikk
Pasientgruppe
Triple negative breast cancer (TNBC), High-risk non-muscle invasive bladder cancer (HR-NMIBC) and Spitzoid melanocytic lesions (SML).
Pasientvolum/datamengde
350 TNBC, 1100 NMIBC and ca 250 SML
Prosjekteier
EU.ITN network
Helseregion
Helse Vest