SYSTEMS AND METHODS FOR ASSESSING LIVER PATHOLOGY
개요
발명자
Amaro N. Taylor-Weiner; Harsha Vardhan Pokkalla; Hunter L. Elliott; Benjamin P. Glass; Ilan N. Wapinski; Aditya Khosla; Murray Resnick; Michael C. Montalto; Andrew H. Beck; Zahil Shanis; Aryan Pedawi; Quang Huy Le; Jason K. Wang; Maryam Pouryahya; Kenneth Knute Leidal; Oscar M. Carrasco-Zevallos; Dinkar Juyal; Charles Biddle-Snead; Katy Wack
IPC 분류
CPC 분류
In some aspects, the described systems and methods provide for a method for training a deep learning model to assess liver pathology, including accessing annotated liver pathology images associated with a group of patients in one or more randomized controlled clinical trials of nonalcoholic steatohepatitis therapy, each of the annotated liver pathology images including at least one annotation describing one or more tissue characteristic categories for a portion of the image, and training the deep learning model based on the annotated liver pathology images to predict the tissue characteristic categories, selected from a group comprising steatosis, lobular inflammation, hepatocyte ballooning, and fibrosis stage.
원문 (중국어)
In some aspects, the described systems and methods provide for a method for training a deep learning model to assess liver pathology, including accessing annotated liver pathology images associated with a group of patients in one or more randomized controlled clinical trials of nonalcoholic steatohepatitis therapy, each of the annotated liver pathology images including at least one annotation describing one or more tissue characteristic categories for a portion of the image, and training the deep learning model based on the annotated liver pathology images to predict the tissue characteristic categories, selected from a group comprising steatosis, lobular inflammation, hepatocyte ballooning, and fibrosis stage.