Fig. 1.

Overview of datasets, methods and models. Three named entity recognizers (NER) identify and normalize brain region mentions: BAMS and ABA (lexical-based) and BraiNER (machine learning-based). Three different extractors predict the connectivity probability of brain region co-occurrences: Filters takes a top–down filtering approach, Kernel is a machine learning-based classifier and Rules consists of hand-written extraction rules. Connectivity results are presented in a searchable web interface. In the future, feedback from the interface can be used to retrain the NERs and extractors for continuous model improvement