Interests
- Radiomics
- Pathomics
- AutoML
- Meta-Learning
- Multimodal machine learning
- Oncology
- Trustworthy AI
- Value-based AI
- Soft-tissue tumors / sarcoma
- Liver cancer
- Colorectal liver metastases
- Open Data
Education
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PhD Streamlined Quantitative Imaging Biomarker Development, 2022
Erasmus Medical Center
Biography
Martijn Starmans is assistant professor leading the AI for Integrated Diagnostics (AIID) research line, with a joint 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 was part of the MICCAI 2024 organization committee as one of the two first ever Open Data chairs. To promote sharing of medical imaging data, he organized the first ever Open Data Event at MICCAI 2024, with a focus on underrepresented diseases and populations, with for this year special attention for African datasets. To facilitate sharing of data, he established the AFRICAI repository, which other resources can use to make data FAIR. He is also African Open Data Chair of the AFRICAI MICCAI Special Interest Group.
Martijn is one of the initiators and PIs 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.
Martijn is involved in various large European projects. He 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, and also work package leader of the Horizon 2021 EOSC4Cancer consortium. Additionally, he is external advisor of RadioVal, and member of the AI4HI AI Development working group, and of EUCAIM. He closely collaboraties with the BCN-AIM lab of Prof. Karim Lekadir at the University of Barcelona, which he also visited in 2023 for 4 months.
Lastly, Martijn also specifically focusses on Trustworthy AI to go beyond technical performance and facilitatie deployment to clinical practice. A good illustration of this is his work as co-lead on FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare. To this end, his group researches value-based AI in radiology. He is also part of the Trustworthy AI for MRI ICAI LAB.
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.