Martijn Starmans is assistant professor leading the AI for Integrated Diagnostics (AIID) research line, with a dual appointment at the Biomedical Imaging Group Rotterdam (BIGR) (Dept. of Radiology & Nuclear Medicine) and PHANTOM group (Department of Pathology) of the Erasmus MC (Rotterdam, the Netherlands). His main research interest is the use of AI to improve the diagnostic work-up through integrated diagnostics, focussed on radiology (“radiomics”) and pathology (“pathomics”). Specifically, he develops multi-modal machine learning methods to simultanously co-learn from both modalities (“radiopathomics”), and automated machine learning and meta-learning methods to generalize these methods across clinial applications. For this idea, he received an NWO AiNed Personal Fellowship Grant. He works on a variety of clinical applications, mainly oncology (e.g. sarcoma, liver cancer, colorectal cancer, bladder cancer, melanoma, cardiology, neuroendocrine tumors).
Collaborations
Martijn is involved in various working groups and is leader of the platform work package of the Horizon 2020 EuCanImage consortium: Towards a European cancer imaging platform for enhanced Artificial Intelligence in oncology. In this context, he visited the AI in Medicine group of Prof. Dr. Karim Lekadir at the University of Barcelona for four months. He is also leader of harmonization and integration work package the Horizon Infro EOSC4Cancer consortium, in wich he is harmonizing and integrating data, data models, and data repositories from various modalities.
He is one of the initiators of the Sarcoma Artificial Intelligence (SAI) consortium (grant awarded), the Liver AI (LAI) consortium (grant awarded), and project lead of the Colorectal Liver Metastes AI (COLIMA) consortium (grant submitted). In these consortia, in total 51 clinical centers, companies, professional- and patient associations from 18 countries are united. Additionally, he is external advisor of RadioVal, and member of EUCAIM. He has been a visiting researcher of the BCN-AIM lab of the University of Barcelona.
He is one of the Open Data Chairs of MICCAI 2024.
PhD Degree
Martijn obtained his PhD degree ‘‘cum laude’’ on February 1 2022 at the Erasmus Medical Center Rotterdam with his thesis titled Streamlined Quantitative Imaging Biomarker Development: Generalization of radiomics through automated machine learning. Following his passion to efficiently and automatically optimize routines, he developed an adaptive radiomics framework using automated machine learning, described in this paper. He collaborated with a large number of clinicians to develop radiomics biomarkers in a wide variety of clinical applications.
Download my PhD Thesis.