Jul 27, 2023 Artificial Intelligence (AI) and Machine Learning (ML) can have a significant impact on healthcare 3D printing. Here are some ways AI and ML can be used to improve healthcare 3D printing: 1) Design optimization: AI and ML can help optimize the design of 3D-printed medical devices and implants. Machine learning algorithms can analyze large amounts of data and generate designs that are more efficient, durable, and cost-effective. 2) Predictive maintenance: AI can monitor 3D printers and predict when maintenance or repairs are needed. This can help avoid downtime and ensure that medical devices and implants are produced consistently and with high quality. 3) Quality control: AI and ML algorithms can be used to analyze 3D-printed medical devices and implants and detect defects or inconsistencies that may not be visible to the naked eye. This can help ensure that products are safe and effective. 4) Patient-specific modeling: AI and ML can be used to generate patient-specific models for 3D-printed implants and prosthetics. By analyzing patient data, AI can create models that fit each patient’s unique anatomy, resulting in a better fit and improved outcomes. 5) Precision medicine: AI and ML can be used to analyze patient data and predict which treatments will be most effective for each patient. This information can be used to guide the design and production of 3D-printed medical devices and implants that are tailored to each patient’s specific needs. Overall, AI and ML can help healthcare 3D printing produce more personalized and effective medical devices and implants, reduce costs, and improve patient outcomes. In this upcoming virtual event, join a group of movers and shakers in the field of healthcare 3D printing and bioprinting, AR/VR, leveraging AI/ML as a core technology (including LLM) to push the boundaries in their products, services, and research.
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Speakers:
Filippos Tourlomousis
Filippos Tourlomousis is the founder of Superlabs, Greece’s first private research accelerator with internally developed ideas in the field of advanced materials and manufacturing. In addition to that, Filippos is the Chief Scientist of “Superlabs, The Laboratory for Autonomous Science” at NCSR Demokritos funded by the EU Resilience and Recovery Fund (Greece 2.0). His main research interests lie in the field of intelligence and robotics infrastructure for self-driving materials science labs of the future (a.k.a. “robot scientists”). He is developing AI-driven autonomous materials engineering platforms that include novel 3D printing methodologies for the fabrication of lattice structures with resolutions spanning microns to cm length scales for healthcare and sustainability applications. With these new tools he has demonstrated a wide range of material systems ranging from 3D microscale biomaterial scaffolds capable of programming stem cell replication by pure manipulation of cell shape, regenerative packaging materials for the circular economy to large-scale metamaterial morphing robots for hydrodynamic applications. Filippos is an E14-fund fellow and the founder/CEO of Biological Lattice Industries, an early-stage biotechnology company that is developing an AI-driven robotic biofabrication platform for tissue engineering and regenerative medicine applications. In addition to that, he is the lead AI & ML engineer for Materiom, a non-profit organization that provides open data on how to make materials that nourish local economies and ecologies funded by Google’s Impact Challenge on Climate fund.. Filippos holds research affiliations with the Highly Filled Materials Institute (NJ, USA), where he completed his PhD and got the Excellence in Research Award for his contributions in processing of complex fluids. He also holds a research affiliation with the MIT Center for Bits and Atoms (CBA), where he was a Postdoctoral researcher for 4 years before joining Demokritos. Filippos has published in prestigious journals such as Science Advances and Microsystems & Nanoengineering, Nature. His work has been featured in Wired, the Economist, Nature Publishing Group, Nature China, MIT News, and the Vanguard by GE. Lastly, he has served as a reviewer for established journals such as Advanced Materials, Advanced Functional Materials, Advanced Engineering Materials, Biofabrication and others.
Kerim Genc
Kerim Genc is a Staff Product Manager for the Simpleware Group at Synopsys. He has expertise in patient specific image-based workflows for Surgical Planning and 3D Printing. He is responsible for business development, strategy, strategic partnerships, and technical marketing content development. Kerim has a Ph.D. as well as a master’s degree in biomedical engineering from Case Western Reserve University.
Jesse Courtier, MD
Jesse Courtier, MD, is the Chief of Pediatric Radiology at UCSF Benioff Children’s Hospital, San Francisco, and a Clinical Professor in the UCSF Department of Radiology & Biomedical Imaging. He is co-Founder of Sira Medical. A UCSF spinout which is focused on development of Augmented Reality software for medical education, training, and preoperative planning. Dr. Courtiers is an award winning medical educator and author of more than 70 peer reviewed publications with over 2400+ citations. His primary research interests include the investigation of augmented reality applications in medical imaging for use in training and surgical planning.
Matthew Kavanagh
Matthew Kavanagh is an Algorithmic Engineer at the Hyperganic Group, focusing on the deployment of AI tools to improve the accessibility and speed at which complex engineering designs can be made using the Hyperganic software. Matthew specialised in biomaterials, nanomaterials and 3D printing when obtaining his master’s degree in Materials Science and Engineering from Imperial College London. His thesis focused on mechanical applications of architectured metamaterials fabricated via additive manufacturing. in 2022, Matthew joined Hyperganic in Singapore and has carried out research on the application of machine learning in the design for additive manufacturing space. His latest work is centered on the upcoming release of a ‘Text-to-3D’ AI tool that aims to enable users to describe design alterations using natural language when integrated with Hyperganic’s software.
Moderator:
Dr. Jenny Chen
Dr. Jenny Chen is trained as a neuroradiologist, and founder/CEO of 3DHEALS. Her main interests include next-generation education, 3D printing in the healthcare sector, automated biology, and artificial intelligence. She is an angel investor who invests in Pitch3D companies.
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