Speakers
Dr. Ir. Colin Jacobs
Colin Jacobs is a leading researcher in artificial intelligence and medical imaging, with a strong focus on lung cancer detection and pulmonary diseases. His expertise lies in the development and validation of machine learning algorithms for radiology applications, aiming to enhance early disease detection and improve patient outcomes. He is actively involved in international research collaborations and contributes to the advancement of AI-driven healthcare solutions.
Dr. Kicky van Leeuwen
Kicky van Leeuwen is a market expert in AI solutions for radiology and healthcare. She founded Health AI Register, a globally used platform offering insights into commercial AI software solutions. She co-leads Romion Health to drive the responsible adoption of AI by advising and educating on medical AI procurement and implementation throughout Europe. Previously, she completed a PhD at Radboud University Medical Center, on the validation and implementation of commercial AI solutions in radiology.
Prof. Dr. Niels van Royen, MD
Prof. Dr. Niels van Royen is a full professor and head of the Cardiology Department at Radboud University Medical Center (Radboudumc) in Nijmegen, Netherlands. He is affiliated with the Radboud Institute for Molecular Life Sciences, focusing on the Vascular Damage theme. Prof. van Royen's research primarily centers on translational studies related to ischemic heart disease, collateral artery growth, and the phenomenon of no-reflow. He has initiated several multicenter clinical trials, including the TRANSIENT, COACT, REDUCE-MVI, and iMODERN trials, which explore the timing of interventional procedures and the use of intracoronary physiology to guide interventions in both stable coronary artery disease and acute coronary syndromes.
Joeri Huigen
Joeri Huigen serves as a Territory Manager in the Vascular division at Abbott, a global healthcare company. Based in Zwolle, Netherlands, he has been with Abbott since 2022, bringing over 3 years of experience in this role. His expertise lies in sales and management within the vascular and endovascular medical devices sector.
Natalie ter Hoeve
Natalie ter Hoeve is a pathologist assistant at the University Medical Center Utrecht (UMCU), actively involved in integrating artificial intelligence (AI) into pathology to enhance diagnostic accuracy and efficiency. She co-authored the CONFIDENT-trial protocol, a study exploring the benefits of AI-assisted workflows in detecting prostate and breast cancer while maintaining diagnostic safety standards. Additionally, she contributed to research on deep learning-supported mitosis counting in breast cancer grading, demonstrating the potential of AI to improve prognostic assessments in clinical workflows.
Gabriele Bani
Gabriele Bani is an AI Engineer at Ellogon.AI, a company specializing in developing artificial intelligence solutions for pathology. He holds a Master's degree in Artificial Intelligence from the University of Amsterdam and has a background in Computer Science, including participation in an Erasmus+ Exchange Programme at the University of Groningen. Before joining Ellogon.AI, Gabriele founded Intrical AI, a tech startup that utilized AI and Natural Language Processing to enhance the research processes of M&A analysts. In his current role at Ellogon.AI, he focuses on creating state-of-the-art AI models aimed at improving diagnostic accuracy and efficiency in pathology.
Dr. Steven Schalekamp, MD
Steven Schalekamp is a radiologist at Radboudumc with a focus on chest imaging and the clinical application of AI in radiology. His research examines the validation and real-world impact of AI tools, including their regulatory claims and evidence base. He has led key studies revealing that many CE-marked AI products lack clear intended use or robust clinical validation. He also co-authored work showing that AI can safely identify normal chest X-rays, helping reduce radiologist workload. His work bridges clinical practice and critical evaluation of AI technologies in healthcare.
Daniel Drieling
Daniel Frieling is a product manager at MeVis Medical Solutions AG, where he has contributed to the development and delivery of advanced medical imaging software for over 17 years. With a background in computer science and a strong focus on information systems, Daniel brings extensive experience in product development, IT project management, and clinical application delivery. His work supports the integration of innovative imaging solutions into clinical workflows, enhancing diagnostic precision and patient care.
Dr. Ir. Hanneke Bluemink
Hanneke Bluemink is a medical physicist at Catharina Hospital in Eindhoven, specializing in AI-driven radiotherapy planning. Her work focuses on using deep learning to automate treatment planning for breast cancer, improving both speed and consistency. She co-authored studies showing that AI-generated plans can match clinical quality while saving significant time, and she supervises research on AI-based segmentation and planning in radiotherapy.
Dennie Fransen
Dennie Fransen is an Application Specialist at RaySearch Laboratories, focusing on the development and optimization of radiation therapy treatment planning systems. Prior to this, he served as a Senior Radiation Therapy Technologist at Holland Proton Therapy Centre (HollandPTC). In 2018, Fransen achieved the highest score in the proton category of the World Championships of Treatment Planning, utilizing RayStation software. His expertise lies in leveraging advanced planning techniques to enhance the quality and efficiency of radiation therapy treatments.
Marja de Waal
Marja de Waal is a clinical informatician at Radboud University Medical Center (Radboudumc) in Nijmegen, Netherlands, with extensive experience in the healthcare sector, particularly in medical imaging. She has played a pivotal role in integrating artificial intelligence (AI) solutions into clinical practice. Notably, she initiated a pilot project evaluating Autoscriber's AI-driven digital scribe technology within Radboudumc's EPIC Electronic Health Record system. This three-month pilot involved ten medical specialists assessing the impact of ambient listening technology on clinical documentation, aiming to enhance workflow efficiency and reduce physician burnout.
Dr. Martijn Bauer, MD
Martijn P. Bauer is an internist at Leiden University Medical Center (LUMC) and serves as the Chief Medical Information Officer (CMIO) at Autoscriber. He played a pivotal role in initiating the development of Autoscriber within LUMC's Internal Medicine department, recognizing the potential of artificial intelligence to enhance clinical note-taking. Bauer has also contributed to research on the impact of digital scribe systems on clinical documentation efficiency and quality.
Prof. Dr. Bram van Ginneken
Bram van Ginneken is a globally recognized expert in medical image analysis and artificial intelligence. As a professor at Radboudumc, he leads groundbreaking research in deep learning applications for radiology, focusing on automated image interpretation and AI-assisted diagnostics. His work has significantly contributed to advancements in lung cancer detection, tuberculosis screening, and broader AI-driven imaging solutions in healthcare.
Robert Breas
Robert Breas specializes in healthcare IT infrastructure, data management, and the integration of digital technologies in medical imaging. With a deep understanding of IT systems and clinical workflows, he ensures that imaging data is effectively processed, stored, and utilized for research and patient care. His work as a senior consultant facilitates seamless collaboration between clinicians, researchers, and IT professionals, enhancing efficiency and innovation in the medical field.