Figure 2
From: Classification of Paediatric Inflammatory Bowel Disease using Machine Learning
Dimensionality reduction approaches and hierarchical clustering of PIBD data. (A,B) Principal component analysis (A) and multidimensional scaling (B) of clinical data from 239 PIBD patients. The first three PCA components account for 52.2% of the total variance. Important note – UC/CD/IBDU diagnoses were used only to retrospectively colour data points and were not included in actual modelling. (C) Heatmap of endoscopic and histological tissue abnormalities in PIBD patients. Abnormal manifestations are shown in orange, normal in light blue and missing data in white. Asterisks indicate histology features. Ascending colon, transverse colon and descending colon labels were shortened to A-Colon, T-Colon and D-Colon respectively. Left hand side bar shows the referred diagnosis: CD in red, UC in blue, IBDU in yellow. Again, UC/CD/IBDU diagnoses were not used to model data but only to retrospectively colour each element. The top bar shows the type of investigation: histology in white, endoscopy in black. Identified colorectal groups are shown by dashed boxes and labelled from one (i) to four (iv). (D) Box and whisker plot depicting C-reactive protein (CRP) levels recorded at diagnosis across the four identified groups. Each box represents data from the first (bottom edge) and the third (top edge) quartile. Red bars and numbers are the median CRP level. Dashed whiskers show the lowest and highest CRP within each group. Black circles are outlier data points.
