![]() ![]() “The question is, how do we combine all these data to try and understand fundamental human systems and disease?” “In the medical domain, understanding human systems depends on analyzing huge amounts of very different types of data,” said Pinaki Sarder, Ph.D., senior author on the paper and associate professor of pathology and anatomical sciences in the Jacobs School of Medicine and Biomedical Sciences. The project is an example of how advanced computational capabilities are allowing scientists to glean new information from complex images of anatomical structures. The cloud-based tool, called the “PodoSighter,” is described in a paper in the Journal of the American Society of Nephrology the research is being highlighted on the cover of the journal’s November issue. Now, University at Buffalo researchers have leveraged the power of digital pathology and computational modeling to develop a new approach to detecting and quantifying podocytes. Those changes are key indicators of the ultimately devastating damage that end-stage renal disease can cause, but these specialized cells are difficult to detect. ![]() In the early stages of kidney disease, a specialized type of kidney cell called the podocyte undergoes damaging changes in both its structure and function. Journal is highlighting this artificial intelligence advance on the cover of the November issue
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |