Fig. 1: Visualization of key concepts.
From: AI-QuIC machine learning for automated detection of misfolded proteins in seed amplification assays
a Example graph of the RT-QuIC data from a single reaction with the source of Time to Threshold (TTT), Rate of Amyloid Formation (RAF), Max Slope (MS), and Max Point Ratio (MPR) highlighted. The different phases of the reaction are identified with a visual of how the monomers form a fibril, increasing the fluorescence. b Diagram of the multilayer perceptron used in this study with 65 input features. The network also includes 3 hidden layers, each with 65 neurons and a single output layer with 3 classes. c Flowchart of how the data is processed in the study.
