More than € 4,4 million granted for the 4th Hanarth Fonds call!

The Hanarth Fonds received 37 financing applications during the 2022 call. Following a careful assessment process, it has been determined that in 2023, 11 projects and 2 fellowships will be funded by the Hanarth Fonds.

The Scientific Advisory Board (WAR) and expert (international) reviewers have assessed the proposals on criteria such as feasibility and quality of the proposal, the experience of the applicant and whether the application is in accordance with the purpose of the Hanarth Fonds. Based on all assessments, the Hanarth Fonds Board has made a well-considered financing decision.

Granted research projects 2022

Below you will find the research projects that have been granted funding*. Soon you will find a link to the summaries of these research projects on this page as well.

• Artificial intelligence-based phenotyping of metastatic renal cell carcinoma to better understand (pseudo)progression under immune checkpoint inhibition
  Bart de Keizer
  UMC Utrecht
  
  
• Artificial Intelligence for Diagnosis of Cutaneous Lymphomas – the AID-CLYM study 
  Anne-Roos Schrader
  LUMC
  
  
• Finding the needle in the haystack: Using artificial intelligence to identify histogenomic biomarkers for metastatic cutaneous squamous cell carcinoma
  Marlies Wakkee
  Erasmus MC
  
  
• Using geometric deep learning to identify MHC-II peptide vaccine candidates for CMMRD patients    
  Jolanda de Vries, co-aanvrager Li Xue
  Radboudumc
  
  
• INTelligent computeR-Aided Surgical gUidance for Robot-assisted surGEry – the INTRA-SURGE-project for the future of surgery
  Jelle Ruurda
  UMC Utrecht
  
  
• Machine Learning to support Clinical Decision Making in Vestibular Schwannoma (MLSCHWAN)    
  Marius Staring
  LUMC
  
  
• Deep learning to Enhance Therapeutic Outcomes and toXicity for LUNG cancer patients (DETOX-LUNG)    
  Lisanne van Dijk
  UMC Groningen
  
  
• Artificial intelligence for histopathological classification and recurrence prediction of thymic epithelial tumors
  Stephanie Peeters
  Maastro
  
  
• GLIOCARE: Glioma Imaging Omitting Contrast through Artificial intelligence and Risk Evaluation Type of research
  Vera Catharina Keil
  Amsterdam UMC
  
  
• Triage of Patients with High-risk Oral Squamous cell Carcinoma using Artificial Intelligence (TOSCA)
  Kenneth Gilhuijs
  UMC Utrecht
  
  
• Cost savings in pathology by AI: prospective clinical trials paving the way for AI implementation
  Paul van Diest
  UMC Utrecht