GPI Seminar Series: Towards skin disease recognition using deep learning (Jul 26th, 2018)
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Adrià Romero, Deep Learning and Computer Vision R&D |
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Albert Jiménez, Deep Learning and Computer Vision Researcher & Developer |
Two UPC ETSETB alumni, who will present their experience in a medical-oriented Canadian start-up Triage
Abstract:Skin disorders are one of the most common reasons why patients visit their primary care physicians. 1 in 3 cancer diagnoses is skin cancer and 1 in 5 Americans will develop skin cancer in their lifetime. The average wait time to see a dermatologist in the United States is 1 month and even greater in other parts of the world. In that time skin disorders can worsen or become life threatening.
The recent emergence of machine learning and deep learning methods for medical image analysis has enabled the development of intelligent medical imaging-based diagnosis systems that can assist physicians in making better decisions about a patient’s health. In particular, skin imaging is a field where these new methods can be applied with a high rate of success.
In this talk you will learn how Triage, a Toronto based startup is using deep learning to diagnose any skin disease through real case studies, few months prior to become one of the first healthcare companies using AI to be approved by the U.S. Food & Drugs Administration.
Short Bios:
Adrià Romero Lopez:
Adrià is applying machine learning and deep learning algorithms to analyze medical images. He graduated in Audiovisual Engineering Systems Degree at Polytechnic University of Catalonia, before completing his Bachelor’s thesis with Honours (and recently awarded as Best Telecommunications BSc thesis 2016-2017) applying deep learning to skin lesion classification at Florida Atlantic University under the supervision of Dr. Oge Marques and Dr. Xavier Giró-i-Nieto. He is also the author of several research publications in the medical imaging field which includes the SIIM 2017 Annual Meeting and 13th IASTED International Conference. Currently his focus is in Machine Learning and Computer Vision to diagnose skin disorders and skin cancer at Triage Technologies, a Canadian startup based in TorontoManel Baradad completed his Bachelor's and Master's degrees at TelecomBCN, conducting his Master's thesis at CSAIL (MIT), under the supervision of professor Antonio Torralba. He will join CSAIL as a graduate student this fall.
Albert Jimenez Sanfiz:
Albert combines his knowledge in deep learning and computer vision to design algorithms to recognize skin lesions. He began his career at Data-61, Australia’s leading data innovation group under the supervision of José Álvarez (former Yann LeCun’s post-doc). During this time, he was also completing his M.Sc. thesis under the supervision of Xavier Giró at the Polytechnical University of Catalunya. There he worked on applying deep learning to image retrieval, ending with a paper accepted in the BMVC2017 Conference and Honours Degree. Albert holds a BSc and a MSc in Electrical Engineering by the UPC with special focus on the topics on Machine Learning, Computer Vision and Speech technologies.