R scripts for predicting ulcerative colitis endoscopic activity through standard clinico-biological parameters using three neural network models are found in the files provided. First binary model to
Background : The infodemic we are experiencing with AI related publications in healthcare is unparalleled. The excitement and fear surrounding the adoption of rapidly evolving AI in healthcar
The samples are a part of a study aiming at diagnosing ulcerative colitis from genome-wide gene expression analysis of the colonic mucosa. Colonic mucosal samples were collected as endoscopic pinch bi
The data is derived from Incopat, and is obtained by using the search formula "(AP-OR=(Chinese Academy of Sciences)) AND (AD=[20030101 TO 20221231])", with 10917 positive samples and 22652 negative sa
The datasets used and analyzed are publicly available data from GEO [GSE 92415 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE92415), GSE 87473 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?
