A Cloud-Based Infrastructure for Feedback-Driven Training and Image Recognition.
Advanced techniques in machine learning combined with scalable "cloud" computing infrastructure are driving the creation of new and innovative health diagnostic applications. We describe a service and application for performing image training and recognition, tailored to dermatology and melanoma identification. The system implements new machine learning approaches to provide a feedback-driven training loop. This training sequence enhances classification performance by incrementally retraining the classifier model from expert responses. To easily provide this application and associated web service to clinical practices, we also describe a scalable cloud infrastructure, deployable in public cloud infrastructure and private, on-premise systems.
IBM Research - Australia, Carlton, VIC, Australia.
Mani
M
Abedini
IBM Research - Australia, Carlton, VIC, Australia.
Stefan
S
von Cavallar
IBM Research - Australia, Carlton, VIC, Australia.
Rajib
R
Chakravorty
IBM Research - Australia, Carlton, VIC, Australia.
Matthew
M
Davis
IBM Research - Australia, Carlton, VIC, Australia.
Rahil
R
Garnavi
D000465:Algorithms; D000067917:Cloud Computing; D046169:Dermoscopy / Q000379:methods; D005103:Expert Systems; D005246:Feedback; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D000069550:Machine Learning; D008545:Melanoma / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods; D012878:Skin Neoplasms / Q000473:pathology*; D014584:User-Computer Interface