Report summary

For Columbia University Department of Biomedical Informatics in 2018-2020, the graph shows 14 visible PIs and 10 internal PI collaborations. The main research signal is Biochemistry, Genetics and Molecular Biology as the leading field (23% of slots across 7 PIs; 7 labels), Molecular Biology as the leading subfield (20% of slots across 7 PIs; 7 labels), and Biomedical Text Mining and Ontologies as the leading topic (10% of slots across 4 PIs; 4 labels). The network looks reasonably well-rounded, with visible collaboration groups but not so much concentration that one field explains the whole department. The most prominent PIs by weighted works are Chunhua Weng (20.2 weighted works; Biomedical Text Mining and Ontologies, Machine Learning in Healthcare). The clearest collaboration lines are Suzanne Bakken and David K. Vawdrey (6 shared works, weight 2.4); Nicholas P. Tatonetti and David K. Vawdrey (4 shared works, weight 2.2). The strongest breakdown groups are group 1 with 8 PIs, 10 internal connections, weight 10.8, around Molecular Biology, Health Information Management, Artificial Intelligence, led by Chunhua Weng, Suzanne Bakken, Nicholas P. Tatonetti.