Aiforia, a leading provider of deep learning artificial intelligence (AI) solutions for image analysis across a variety of medical domains, announces its newly formed Scientific Advisory Board. The four advisors represent world-class expertise in clinical diagnostics, personalized medicine, digital and computational pathology.
The Scientific Advisory Board will support Aiforia's mission in providing the most powerful tools for AI-assisted analysis to enhance the translation of medical images into data and discoveries in all realms of healthcare. From scientific research to clinical diagnostics, Aiforia aims to outfit healthcare professionals with the digital solutions they need for the shifting landscape of medicine.
The Aiforia Scientific Advisory Board is composed of the following experts:
Marilyn Bui, MD, PhD,is a Professor of Pathology and the Scientific Director of Analytic Microscopy Core at Moffitt Cancer Center inthe United States. An impactful leader in pathology, she notably served as the President of the Digital Pathology Association in 2019.
Anant Madabhushi, PhD,is an endowed Professor of Biomedical Engineering atCase Western Reserve UniversityinCleveland, Ohiointhe United Statesand holds the position of the Director of the university's Center for Computational Imaging and Personalized Diagnostics.
Yukako Yagi, PhD, is the Director of Pathology Digital Imaging at Memorial Sloan Kettering Cancer Center (MSKCC) inNew Yorkinthe United States. She has held esteemed positions at theUniversity of PittsburghMedical Center,Harvard Medical School, and as the Director of the Pathology Imaging and Communication Technology Center atMassachusettsGeneral Hospital.
Jonathan Knowles, PhD,is a global opinion leader in personalized medicine. He is currently a visiting professor at theUniversity of Oxford, UK and serves on the board of a number of pharma and biotech companies, most notably he was the President of Group Research for the Roche Group for 12 years.
"I am impressed with Aiforia's focus on developing image analysis and machine learning tools to help democratize the process of deep learning and AI," explains Aiforia Advisory Board member Dr.Anant Madabhushi: "Aiforia's focus on making these tools accessible to the naive user, to help them quickly and easily stand up their own deep learning networks for pathology without substantial technical know-how is very compelling. This will allow for much larger uptick in users of AI in computational pathology and might even help facilitate development of custom-made clinical applications."
"We are excited and humbled to work with a group of such renowned experts to support Aiforia's mission in providing AI-powered image analysis solutions to improve workflow efficiency and scalability in healthcare; enabling new discoveries, better-informed decisions, and more personalized patient care," describes Aiforia's CEOJukka Tapaninen.