Dr. Joseph Stancanello | Medical | Excellence in Innovation
Vicepresident, Elekta, France
Joseph Stancanello (b. 09/03/1976) is a global healthcare technology leader with a Ph.D. in Bioengineering from Politecnico di Milano. 🌍 With executive roles across top medical companies like Elekta, Guerbet, and Siemens Healthcare, he has driven innovation in radiotherapy and imaging systems. ✨ An expert in P&L management, business development, and R&D, Joseph bridges clinical, regulatory, and business needs. He excels in defining value propositions and fostering innovation through strategic partnerships and mergers. 💡 Beyond his corporate impact, he reviews cancer research proposals for European TRANSCAN calls and AI funding for the Italian Ministry of Research. 🧠 His expertise spans AI, radiotherapy, and advanced imaging technologies, addressing both patient care and market growth.
Publication Profile
Education🎓
Joseph Stancanello has a Ph.D. in Bioengineering and an MSc in Biomedical Engineering, both magna cum laude from Politecnico di Milano. 🌟 He also earned an Executive MBA from MIP Politecnico di Milano, securing the 2010 Best Dissertation Prize. 🎖️ His educational foundation includes: Executive education at INSEAD, SDA Bocconi, and MIT-Sloan School of Management. Specialized programs like “Finance for Executives” and “Driving Strategic Innovation. nA classical education background from “Secusio” Liceo in Italy (60/60). Joseph combines technical expertise with business acumen, driving healthcare innovation globally.
Experience 🌍
Joseph Stancanello has over two decades of global healthcare experience: VP Clinical Applications, Elekta (2021–Present): Leads global teams in advancing radiotherapy imaging and therapy solutions. Director of Marketing AI, Guerbet (2019–2021): Launched AI-based cancer diagnostics solutions. CEO, Oncoradiomics (2017–2019): Managed VC fundraising and global business strategies. Leadership roles at GE and Siemens (2007–2015): Spearheaded MRI research, workflows, and innovative imaging techniques.
Awards & Honors🏆
Joseph Stancanello has received multiple accolades for his contributions to healthcare: Best Dissertation Prize, Politecnico di Milano Executive MBA, 2010. Invited reviewer for European TRANSCAN cancer calls and AI projects (2022–2024). Recognized for advancing imaging systems and radiotherapy applications globally.
These achievements underscore his leadership in healthcare technology and research.
Research Focus 🌟
Advanced radiotherapy techniques and imaging for cancer care. 📊 AI in healthcare, focusing on diagnostic and predictive tools Morphological and functional imaging in radiosurgery. Bridging clinical needs with technology innovations to improve patient outcomes His research drives precision medicine and healthcare transformation globally.
Publications
- Evolution of AI in Medical Imaging: The review by Avanzo et al. (2024) emphasizes the integration of computer science principles with machine and deep learning techniques to enhance medical imaging applications.
- Head and Neck Cancer Prognosis: Studies by Wang et al. (2022) and Lombardo et al. (2021) develop convolutional neural network (CNN)-based models for predicting cancer prognosis and metastasis, demonstrating the potential of AI in clinical oncology.
- Radiomics and Deep Learning: The series of works, including a review in Strahlentherapie und Onkologie (2020), explore how combining radiomics and deep learning improves tumor response prediction and radiotherapy outcomes.
- Lung Cancer and Radiomics: Multiple studies, including Avanzo et al. (2021), utilize CT imaging and biologically effective dose data in radiomics to enhance predictive models for robotic lung stereotactic radiation therapy.
- Fibrosis and Dosimetry: Avanzo and colleagues (2020) focus on using machine learning to predict radiation-induced fibrosis, advancing personalized medicine approaches in radiotherapy.
- AI in Hybrid Imaging: Castiglioni et al. (2019) detail how AI-based tools in hybrid imaging facilitate multi-parametric decision-making, underscoring the versatility of AI in various imaging modalities.
- Practical Applications in IOERT: Research on intraoperative electron radiotherapy (Avanzo et al., 2020) addresses dosimetry challenges and tissue inhomogeneities, bridging AI with practical clinical applications.
- Clinical Trials in Breast Cancer: Long-term outcomes of partial breast irradiation trials (Vinante et al., 2019) highlight advancements in treatment protocols facilitated by AI-enhanced imaging analysis.